Genomic Capacities for Reactive Oxygen Species Metabolism Across Marine Phytoplankton

¹ Department of Biology, Mount Allison University, 53 York St., Sackville NB, Canada, E4L 1C9.
² Faculty of Veterinary Medicine, University of Calgary, 3280 Hospital Dr NW, Calgary, AB, T2N 4Z6.
³ Faculty of Computer Science, Dalhousie University, 6050 University Ave, Halifax, NS, B3H 1W5.
⁴ Center Algatech, Laboratory of Photosynthesis, Novohradska 237, Trebon, CZ 37981, Czech Republic.

^✉ Correspondence: Douglas A. Campbell <dcampbel@mta.ca>

XXX Cite this page for logit2prob https://sebastiansauer.github.io/convert_logit2prob/

Abstract

Marine phytoplankton produce and scavenge Reactive Oxygen Species, to support cellular processes, while limiting damaging reactions. Some prokaryotic picophytoplankton have, however, lost all genes encoding scavenging of hydrogen peroxide. Such losses of metabolic function can only apply to Reactive Oxygen Species which potentially traverse the cell membrane, before provoking damaging intracellular reactions. We therefore hypothesized that cell radius influences which elements of Reactive Oxygen Species metabolism are potentially dispensable from a cell. We investigated genomes and transcriptomes from diverse marine eukaryotic phytoplankton, ranging from 0.4 to 44 µm radius, to analyze the genomic allocations encoding enzymes metabolizing Reactive Oxygen Species. Superoxide has high reactivity, short lifetimes and limited membrane permeability. Genes encoding superoxide scavenging were ubiquitous, but the fractional gene allocation decreased with increasing cell radius, consistent with a nearly fixed set of core genes for scavenging superoxide pools. Hydrogen peroxide has lower reactivity, longer intracellular and extracellular lifetimes and readily crosses cell membranes. Genomic allocations to hydrogen peroxide production decrease with increasing cell radius, more than do genomic allocations to scavenging of hydrogen peroxide, consistent with maintenance of ROS homeostasis in the face of slower diffusional losses of hydrogen peroxide from larger cells. Gene allocations to hydrogen peroxide metabolism are positively influenced by capacity for colony formation, suggesting more active hydrogen peroxide metabolism among the closely spaced cells of colonies, compared to single cells; and by the presence of flagella, suggesting an interaction between flagella and maintenance of Reactive Oxygen Species homeostasis. Nitric Oxide has low reactivity, long intracellular and extracellular lifetimes and readily crosses cell membranes. Neither Nitric Oxide production nor scavenging genomic capacities changed with increasing cell radius. Centric vs. pennate diatoms, however, show contrasting gene allocations to nitric oxide metabolism, consistent with diverse roles of nitric oxide across taxa.

Introduction

Phytoplankton cells span a large size range, from picoplankton (<2µm), nanoplankton (2 to 20µm), microplankton (20 to 200µm) to macroplankton (200 to <2000µm) [1]. Cell size interacts with multiple selective pressures, including cellular metabolic rate, light absorption, nutrient uptake, cell nutrient quotas, trophic interactions and diffusional exchanges with the environment [1–5]. Beyond simple size, cells of different shapes differ in surface area to volume ratio. For example, more elongated cells, such as pennate diatoms, have a larger surface area to volume ratio compared to more rounded cells, such as centric diatoms, of equivalent biovolume [6], which can in turn influence diffusional exchanges between cells and their environment.

Characteristics of Reactive Oxygen Species

Phytoplankton both produce and scavenge Reactive Oxygen Species (ROS), both within and outside the cell membrane, enzymatically and non-enzymatically. Some ROS readily cross the cell membrane, connecting intra- and extra-cellular pools. Other ROS rarely cross cell membranes and therefore intra- and extra-cellular pools are at least partially segregated (Table 1).

Table 1: Diffusion and Stability of Different ROS

ROS	ROSSymbol	SeawaterLow_M	SeawaterHigh_M	ConcentrationCitation	DiffusionDistance_nm	DiffusionDistanceCitation	LifetimeLow_s	LifetimeHigh_s	LifetimeCitation	CrossesCellMembrane	CrossesCellMembraneCitation	AbioticProductionLow_Ms-1	AbioticProductionHigh_Ms-1	AbioticProductionRatesCitation	DiffCoef_um2us	DiffCoefCitation
Hydrogen Peroxide	H2O2	1e-09	1e-06	[7,8]	NA	NA	3.6e+03	1.2e+05	[7–9]	Yes	[10–13]	1e-13	1e-11	[14]	1500	[15]
Superoxide	O2•−	1e-12	1e-09	[7,16]	320	[9]	1.0e-03	6.0e+01	[7,16]	No	[17]	1e-14	1e-10	[14]	210	[18]
Nitric Oxide	NO•	1e-12	1e-10	[16,19]	NA	NA	2.0e+00	2.0e+01	[16,20]	Yes	[21]	1e-13	1e-11	[16]	2210	[22]
Hydroxyl Radical	HO•	1e-18	1e-15	[7]	4.5	[9]	1.0e-06	1.0e-06	[7]	No	[23]	3.055556e-22	2.777778e-12	[24]	NA	NA
Singlet Oxygen	1O2	1e-13	1e-14	[25]	82	[9]	1.0e-06	1.0e-06	[9]	NA	NA	NA	NA	NA	2100	[26]
Peroxynitrite	ONOO−	1e-12	1e-11	[16]	NA	NA	1.0e-03	1.0e-03	[16,27]	Yes	[28]	1e-11	1e-09	[16]	NA	NA

Superoxide (O₂^•−), a radical anion generated through the monovalent reduction of O₂ to O₂^•− [29], is present in the oceans at concentrations of 10^-12 to 10^-9 [7,16]. O₂^•− is highly reactive [30] with organic compounds including thiols [31] and with metals [32,33]. As the first ROS in a sequential series of reductions of O₂, O₂^•− is a ‘gateway’ to production of other ROS. O₂^•− is produced both inside and outside a cell, but shows limited diffusion across the hydrophobic cell membrane [17]. Electron transfers to O₂ from the photosynthetic and mitochondrial electron transport chains generate intracellular O₂^•− as a by-product [34–39]. Multiple oxidases (Table 3) reduce O₂ and generate either H₂O [40], or alternately O₂^•− and/or Hydrogen Peroxide (H₂O₂) [41,42]. Biogenic production of extracellular ROS mediated by taxa ranging from heterotrophic bacteria to diatoms is significant in marine environments [7,43–50]. Increasing cell suspension density leads to decreased O₂^•− production per cell [48,51,52]. Some extracellular O₂^•− production likely contributes to cell growth, in that the removal of extracellular ROS from cultures of the heterotrophic bacteria Roseobacter inhibits its growth [51]. O₂^•− in coastal waters is primarily attributable to extracellular production mediated by eukaryotic phytoplankton [53]. In contrast, Prochlorococcus MED4 shows the least extracellular production of O₂^•− among microbes analyzed to date [48]. O₂^•− production patterns can vary even within a genus [47].

Two known enzymes mediate conversion of O₂^•− to H₂O₂; the ubiquitous dismutation of O₂^•− catalyzed by diverse Superoxide Dismutases (SOD) or the less prevalent reduction of O₂^•−, catalyzed by Superoxide Reductase (SOR) at the expense of metabolic reductant. O₂^•− also dismutates spontaneously to produce H₂O₂ and O₂ [54], although [55] found that ~52% of dark O₂^•− production instead likely undergoes oxidation back to O₂. Extracellular production of O₂^•− thus indirectly contributes to extracellular H₂O₂ pools [47,48,56,57].

H₂O₂ is an uncharged compound, present in the ocean at concentrations of 10^-9 to 10^-6 mol L^-1 [7], depending upon location and conditions including temperature, light level, depth of the mixed layer and the concentration of total dissolved organic carbon [58]. In aquatic systems, H₂O₂ has lifetimes of hours to days (Table 1) [7,9]. H₂O₂ passively traverses cell membranes [59], primarily through aquaporins [10–13], allowing exchange of intracellular and extracellular pools of H₂O₂, although cells can maintain a concentration gradient between internal and external H₂O₂ [60].

H₂O₂ is acutely toxic to most cells in the range of 10^-5 to 10^-4 mol L^-1 [59] (Table 1). H₂O₂ can react with thiols and methionine [31] and can interfere with gene expression [61]. Cytotoxic effects of H₂O₂, including lipid damage, are however, primarily caused by H₂O₂ dismutating into the hydroxyl radical, which is strongly oxidative [9].

Multiple different oxidases are important in producing H₂O₂ including glycolate oxidase, NADPH oxidase, oxalate oxidase, amine oxidase [42] and many others (Table 3), but abiotic processes, including rainfall, may be dominant sources of extracellular H₂O₂ in seawater [62–64]. H₂O₂ concentrations in seawater follow a diurnal cycle with a peak at mid-day [58,62,65], suggesting significant direct or indirect photochemical or photobiological generation of H₂O₂. Heterotrophs do not contribute much of the H₂O₂ production but significantly mediate H₂O₂ detoxification [66]. H₂O₂ also decomposes spontaneously, though slowly, into water and oxygen [67], and contributes significantly to the redox cycling of copper and iron in seawater [68,69].

Prochlorococcus and some strains of Synechococcus lack all genes encoding enzymes for scavenging of H₂O₂, and are therefore difficult to grow in axenic cultures, particularly at higher cell densities. Growth and survival of these strains improves when co-cultured with other ‘helper’ bacteria which carry genes for catalase [70–73]. These culture results were found at Prochlorococcus cell densities somewhat higher than typical ocean levels of 1 × 10⁵ to 3 × 10⁵ Prochlorococcus cells ml^-1 [74], where auto-intoxication from metabolism of the Prochlorococcus cell population might be less prevalent [75]. In the open ocean, extracellular H₂O₂ levels generally remain below the acutely cytotoxic threshold of ~1 x 10^-5 M, perhaps partly through activity of co-occuring helper microorganisms that retain capacity to produce catalase [65,70].

Despite its radical nature and ability to react with biomolecules, ^•NO functions widely as a signaling molecule [76,77]. Optimal in vivo concentrations of ^•NO for phytoplankton growth vary significantly across taxa, from 10^-8 to 10^-9 mol extracellular ^•NO L^-1 [78]. ^•NO is produced both biogenically through arginine dependent Nitric Oxide Synthases (NOS) or Nitric Oxide Associated Proteins (NOA) [79], as well as through abiotic processes including nitrite photolysis [80]. Overexpression of ^•NO producing genes in the diatom Phaeodactylum tricornutum results in reduced growth, photosynthetic activity and ability to adhere to surfaces, and thus likely a decrease in biofilm formation [81]. [81] further suggest that ^•NO influences cell motility in that diatoms increase ^•NO production under stressful conditions thereby decreasing cellular adhesion, freeing the cell to find a more suitable habitat to which to adhere. ^•NO can be enzymatically scavenged through Nitric Oxide Dioxygenase (NOD) or Nitric Oxide Reductases (NOR) [82] (Table 3), and may also react non-enzymatically with reduced glutathione (GSH) to form S-nitrosoglutathione (GSNO) [21,83]. Most cellular damage mediated by ^•NO is attributed to the reaction of ^•NO with O₂^•− to produce Peroxinitrite (ONOO⁻). The reaction of ^•NO with O₂^•− to produce ONOO^- is limited by the extracellular concentration of ^•NO and is not a major ^•NO sink in seawater [16].

Other important ROS, Singlet Oxygen (¹O₂), Peroxynitrite (ONOO^-) and Hydroxyl Radical (HO^•) are not known to be directly produced nor scavenged by enzymatic processes [[84]; [59,85–88]. In seawater, HO^• is present in concentrations of 10^-18 to 10^-15 mol L^-1, and has a diffusion distance of only ~4.5 nm before destruction with a lifetime of µs [7,9]. Because of the high reactivity of HO^•, it is unlikely that there are any scavengers dedicated to HO^• specifically [59], although reactions with dissolved organic matter non-specifically scavenge extracellular HO^• [89].

The Black Queen Hypothesis

The Black Queen Hypothesis states that loss of function mutations may proceed so long as some interacting community members retain the function, and the function can occur outside a given cell [90]. The Black Queen Hypothesis was formulated on the basis of Prochlorococcus and H₂O₂. Prochlorococcus (the beneficiary) lost the gene katG encoding an enzyme which scavenges H₂O₂. Instead Prochlorococcus allows H₂O₂ outwards across the cell membrane to be dealt with by community members retaining the capacity to scavenge H₂O₂, thus saving Prochlorococcus the cost of maintaining the genes and metabolism for scavenging H₂O₂ [71,90].

Hypotheses and Significance

Given that ROS show differential abilities to cross cell membranes, and have widely different diffusion distances before destruction, we sought to study whether cell radius, colony formation, flagella or diatom cell shape influence genomic allocations to ROS production and scavenging across diverse marine phytoplankters.

Hypothesis 1 Cell radius across phytoplankton taxa does not influence the fraction of total gene content encoding O₂^•− production, nor scavenging. O₂^•− is highly toxic, and not readily able to cross biological membranes [17], so diffusional losses of O₂^•− from cells are limited and will be little influenced by cell size.

Hypothesis 2 Large phytoplankton allocate a smaller fraction of their total gene content to H₂O₂ and ^•NO production and a larger fraction of their total gene content to H₂O₂ and ^•NO scavenging.

H₂O₂ and ^•NO have relatively low reactivity, with long intracellular and extracellular lifetimes leading to long potential diffusion paths before destruction. Both H₂O₂ and ^•NO are uncharged and readily cross cell membranes (Table 1). Large cells have longer intracellular diffusional paths and a lower surface to volume ratios than do smaller cells [1]. Large cells are thus less prone to diffusional losses of intracellular H₂O₂ and ^•NO. To maintain H₂O₂ and ^•NO homeostasis in the face of slower diffusional losses of H₂O₂ or ^•NO out of the cells to the environment, large phytoplankton may have a smaller fraction of their gene contents for H₂O₂ and ^•NO production. In contrast, loss of function mutations on enzymes that scavenge H₂O₂ and ^•NO would be more deleterious in large cells than in smaller cells [71,90].

Hypothesis 3 Pennate Diatoms allocate a larger fraction of their total gene content to H₂O₂ and ^•NO production, and a smaller fraction of their total gene content to H₂O₂ and ^•NO scavenging than do Centric Diatoms.

Pennate Diatoms have a small minimum radii even at large biovolumes due to their elongated shape [91]. This cell shape of pennate diatoms allows for more diffusion of H₂O₂ and ^•NO across the cell membrane due to the short mean diffusion paths to the cell surface and high surface area to volume ratio. Noting that H₂O₂ and ^•NO are permeable across biological membranes (Table 1). Pennate diatoms may have a larger fraction of their total gene content for H₂O₂ and ^•NO production compared to centric diatoms. In contrast, pennate diatoms may have a smaller fraction of their gene content for H₂O₂ and ^•NO scavenging, compared to centric diatoms.

Hypothesis 4 Colony forming phytoplankton have a smaller fraction of their total gene content encoding H₂O₂ and ^•NO production, and a larger fraction of their total gene content encoding H₂O₂ and ^•NO scavenging. Cell spacing in colony forming phytoplankton is so small that the diffusional spheres of H₂O₂ or ^•NO diffusing outwards from cells overlap with nearby cells [75], thereby shifting the requirements to maintain homeostasis within cells of a colony.

Hypothesis 5 Flagellated phytoplankton have a larger fraction of their total gene content encoding H₂O₂ and ^•NO production, and a smaller fraction of their total gene content encoding H₂O₂ and ^•NO scavenging. Increased motility in flagellated cells allows movement away from cytotoxic levels of H₂O₂ and ^•NO, possibly complementing scavenging.

Our work analyzed the fraction of the total genes in a genome or transcriptome associated with the metabolism of a particular ROS. The presence or absence of genes encoding specific ROS metabolizing enzymes may be caused by genetic drift, or may relate to a selective advantage linked to other metabolites of the same enzyme, rather than an enzymatic role in ROS metabolism, per se. Furthermore, the presence of a gene in a genome does not necessarily mean the encoded enzyme will be active, and closely related enzymes may mediate different activities in different organisms. The influence of non-enzymatic pathways such as carotenoids or tocopherols [42,92,93] may affect the hypotheses listed above, but were beyond the frame of this study.

Methods

Data Dictionary

Table 2 contains a data dictionary of variable names used in our analysis, their definitions and locations in code and data objects.

Bioinformatic Pipeline

We downloaded Genomes and/or Transcriptomes of 146 diverse marine phytoplankton (Table 4) from the National Center for Biotechnology Information (NCBI) [94]; Joint Genome Institute (JGI) [95,96]; iMicrobe [97], European Nucleotide Archive (ENA) [98]; pico-PLAZA [99], 1000 Plants (1KP) [100]; and the Reef Genomics Database [101] (Fig 1).

We implemented an automated pipeline using Snakemake [102] to pass gene sequences from downloaded genomes or transciptomes, in .fasta format, to eggNOG-Mapper 2.0.6 [103,104] and then used the DIAMOND algorithm [105] and the eggNOG 5.0 database [106], to annotate potential orthologs in each analyzed genome or transcriptome, using the following parameters: seed_ortholog_evalue = 0.001, seed_ortholog_score = 60, tax_scope = “auto,” go_evidence = “non-electronic,” query_cover = 20 and subject_cover = 0. The annotation generated for each gene model included (when available): the name of the matching ortholog (coded by eggNOG as ‘seed_eggNOG_ortholog’); E-value (coded by eggNOG as ‘seed_ortholog_evalue’); Score (coded by eggNOG as ‘seed_ortholog_score’); EC number (coded by eggNOG as ‘EC’); Kegg Orthology (KO) number (coded by eggNOG as ‘KEGG_ko’); Kegg Pathway (coded by eggNOG as ‘KEGG_Pathway’); Kegg Module (coded by eggNOG as ‘KEGG_Module’); Kegg Reaction (coded by eggNOG as ‘KEGG_Reaction’); Kegg Reaction Class (coded by eggNOG as ‘KEGG_rclass’); the predicted protein family (coded by eggNOG as ‘PFAMs’); Gene Ontology (GO) annotation (coded by eggNOG as ‘Gos’); as well as a description from eggNOG of the source organism of the matching ortholog (coded by eggNOG as ‘best_og_desc’). Note that comparison of sequences to the eggNOG 5.0 database generates non-supervised orthology annotations, and is subject to error if the underlying eggNOG annotation was inaccurate, or for functionally divergent orthologous gene sequences. The output of automatically annotated orthologs, from each genome or transcriptome, from the bioinformatic pipeline was compiled into one file CombinedHits.csv (to be submitted to the DRYAD database to support alternate analyses) (Fig 1).

Figure 1: Summary Flowchart of Methods.

Overview of Analysis of Annotated Genes

CombinedHits.csv was imported into a data frame (coded as ‘CombinedHits’) for analysis using R [107] running under RStudio [108], using the ‘tidyverse’ [109], ‘broom’ [110], ‘magrittr’ [111], ‘dplyr’ [112], ‘rcompanion’ [113], ‘gmodels’ [114], ‘stats’ [107], ‘AER’ [115] and ‘smatr’ [116] packages. Graphics and tables were generated using the ‘ggplot2’ [117], ‘cowplot’ [118], ‘glue’ [119], ‘kableExtra’ [120], ‘corrplot’ [121], ‘ggfortify’ [122,123], and ‘ggforce’ [124] packages (Fig 1). Formatted outputs were generated from RMarkdown files using the ‘knitr’ [125–127] and ‘bookdown’ [128] packages.

In parallel we assembled metadata from the literature and culture collection databases for each phytoplankter for which we obtained a genome or transcriptome, including the cell radii in µm from 100% of organisms; colony formation for 84% of organisms; cell shape from diatoms from 100% of diatoms; presence or absence of flagella as an index of potential motility from 100% of organisms, the genome size from all genomes and the total number of predicted gene models from 80% of organisms (Table 4); all stored in CellGenomeMetrics.csv (to be submitted to the DRYAD database for alternate analyses) (Fig 1). For organisms for which only transcriptomes were available, we only included datasets for which the total number of detected different transcripts was available, as a proxy for the total number of predicted genes. Strains of brackish origin were included but we did not include obligate freshwater strains in our analyses.

Citations were managed using the Zotero (www.zotero.org) open access reference manager connected to RStudio using the ‘citr’ [129] package. The Zotero library of citations for this paper is available at (https://www.zotero.org/groups/2333131/ros_phytoplankton).

We compared the Enzyme Commission Number (EC number) from CombinedHits to the BRENDA enzyme database [130] to identify enzymes annotated by BRENDA as ‘natural product’ or ‘natural substrate’ for H₂O₂, O₂^•− or ^•NO in vivo (Table 3; Fig 1). We then used the EC Number to filter ‘CombinedHits’ to generate a subset containing only those orthologs encoding enzymes directly mediating metabolism, Production or Scavenging, of H₂O₂ , O₂^•− and ^•NO.

From the ‘CombinedHits’ data frame, we filtered out some enzymes where the BRENDA annotations of ‘natural product’ or ‘natural substrate’ was questionable, in particular:

• Superoxide oxidase (EC:1.10.3.17) carries a BRENDA annotation of ‘natural product’ for O₂^•−, despite the BRENDA citation stating that O₂^•− production from superoxide oxidase was only documented in vitro with an excess of ubiquinone [131].
• D-amino-acid oxidase was removed from counts of genes encoding H₂O₂ production, as the enzyme does not produce H₂O₂ in vivo [132].
• Bacterial non heme ferritin is listed under H₂O₂ production and scavenging as it produces H₂O₂ in the first of a two-step reaction and scavenges H₂O₂ in the second step [133].

From the subset of ‘CombinedHits’ of enzymes annotated for ROS metabolism, we grouped orthologs together by EC number and their Kegg Orthology number (KO number) and determined the occurrences of individual orthologs encoding each EC number, or KO number when EC number was not available, in a given organism. We merged this data subset with CellGenomeMetrics.csv to generate a dataset of genes encoding ROS metabolizing enzymes, as defined by the EC or KO number, along with characteristics of the source organism, combined into ‘MergedData.’

H₂O₂, O₂^•− and ^•NO differ in reactivity, stability, diffusion distance, effects on biomolecules and roles in cell signaling (Table 1). We therefore generated the total gene counts coding for the production or scavenging of each different ROS in a given organism, which were used to generate Poisson or Quasi-Poisson regressions (Fig 1).

Data Validation & Justification of Statistical Analyses

Data from both genomes and transcriptomes were used in this analysis to gain wider representation from more taxa (Fig 11). Data from the taxa with the largest radii were derived wholly from transcriptomes. Aside from the prokaryote genomes, sourced solely from within the 45° north south latitude band, the sampled phytoplankton did not exhibit taxonomic biases in source latitude of isolation, but were primarily coastal (Fig 12). For 40 organisms we had both genomic and transcriptomic data, which we used to test assumptions on data distributions (Fig 15). As expected, data coverage from paired genomes and transcriptomes correlated well. Therefore, when both genomic and transcriptomic data were available from the same organism, we used genomic data in subsequent analyses (Table 4), but we used data from transcriptomes when genomes were not available. We validated the gene annotations generated by the snakemake bioinformatic pipeline by comparing the total number of genes encoding ROS metabolism data from a subset of ‘CombinedHits.csv’ to the total number of genes encoding ROS metabolism data from a manually annotated dataset generated during a pilot project (Fig 13) [134,135].

As expected, Fig 13 shows a significant correlation (Correlation of 0.87, p = 1.6×10^-49) between manually generated ‘ROSGene_count’ and the automated ‘ROSGene_count’ from the snakemake pipeline.

Figure 2: Comparison of log₁₀ of the total number of genes in an organism (‘log_GeneModels_count’) to log₁₀ of the median cell radius in µm (‘log_Radius_um’). Colour corresponds to the taxonomic lineage (‘Phylum’), whereas symbol shape corresponds to the source of the data, whether Genome or Transcriptome (‘Ome’). Citations for data sources are in Supplementary Table S3.

Figure 3: Comparison of log₁₀ of the total number of ribosomal genes in an organism (‘log10(RibosomeCount)’) to log₁₀ of the median cell radius in µm (‘log_Radius_um’). Colour corresponds to the taxonomic lineage (‘Phylum’), whereas symbol shape corresponds to the source of the data, whether Genome or Transcriptome (‘Ome’). Citations for data sources are in Supplementary Table S3.

XXX

MergedData %>% 
  filter(GeneModels_count != "0") %>%
  ggplot(aes(x = log10(RibosomeCount), y = log_GeneModels_count)) +
  ggConvexHull::geom_convexhull(alpha = 0.2, aes(fill = Phylum, color = Phylum)) +
  geom_point(aes(shape = Ome, colour = Phylum), size = 3) +
  scale_colour_manual(values =TaxaColors)+
  scale_fill_manual(values =TaxaColors)+
  scale_shape_manual(values = c(19,1)) +
  theme_bw() +
  coord_flip()+
  scale_x_continuous(limits = c(0,3))+
  scale_y_continuous(limits = c(3,6))+
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text=element_text(size=12),
        axis.title=element_text(size=14),
        aspect.ratio = 1,
        legend.text=element_text(size=10),
        legend.title = element_text(size=12)) +
  labs(x = ~log[10] ~ "(Total Number of Ribosomal Genes)",
       y = ~log[10] ~ "(Total Number of Genes)")

Fig 14 shows that the frequencies of counts of genes encoding the metabolism of O₂^•−, H₂O₂ or ^•NO within an organism are not normally distributed (Shapiro-Wilk Test [136] with a p-value of 6.4×10^-30 for O₂^•− scavenging, 9.4×10^-24 for H₂O₂ production, 5×10^-25 for H₂O₂ scavenging, 1.2×10^-18 for ^•NO production and 1.5×10^-30 for ^•NO scavenging). The frequencies of gene counts instead follow a Poisson distribution. Therefore, for subsequent analyses we used Poisson or Quasi-Poisson regressions to compare the counts of genes that encode the production or scavenging of O₂^•−, H₂O₂ or ^•NO within an organism to log₁₀ of the median cell radius in µm. Code used to produce the Poisson and Quasi-Poisson models is on https://github.com/NaamanOmar/ROS_bioinfo/tree/master/ROSGenomicPatternsAcrossMarinePhytoplankton.

Quasi-Poisson regressions were used when the Poisson regression was over-dispersed (dispersion > 1, p < 0.05) as determined by the ‘AER’ package [115]. A Poisson regression followed by a chi-squared test, or a Quasi-Poisson regression followed by an F test, was used to obtain p-values [137], with an alpha value of ≤0.05 as the threshold for statistical significance of regressions.

The total number of genes in each organism increased with the median cell radius, and also varied among the taxonomic lineages (coded as ‘Phylum’) (Fig 2). Taxonomic lineage, in turn, interacts strongly with the median cell radius. For our analyses, we sought to detect effects of cell radius upon the fraction of total genes encoding ROS metabolism. We therefore included an offset of the total number of genes in the organism in the Poisson or Quasi-Poisson regressions, which is equivalent to normalizing the number of genes encoding the production or scavenging of H₂O₂, O₂^•− or ^•NO, to the total number of genes in the organism (‘GeneModel_count’). We thereby offset the general increase in ‘GeneModel_count’ with increasing the median cell radius. Because of the strong interaction between the median cell radius and taxonomic lineage (Fig 11), we did not include Phylum as a co-variate in our subsequent regressions of normalized gene counts vs. median cell radius. Thus, we did not analyze specific influences of Phylum upon gene counts for ROS metabolism. Poisson or Quasi-Poisson regressions were run both with or without ‘Colony’ and ‘Flagella’ as co-variates.

To further investigate possible influences of colony formation, the presence of flagella or diatom cell shape (pennate or centric), upon the fraction of genes that encode the metabolism of H₂O₂, O₂^•− or ^•NO, we used a Wilcoxon test [138].

Results and Discussion

Superoxide

Although there are enzymes producing O₂^•− [139], in the marine phytoplankton genomes and transcriptomes that we analysed, we did not detect any genes that encode for enzymes (Table 3) specifically producing O₂^•−, based on the BRENDA annotation of O₂^•− scavenging. It is however worth noting the presence of genes annotated as encoding NADPH Oxidase (NOX) in some phytoplankton genomes. NOX can produce either H₂O₂ or O₂^•− depending on the NOX isoform. NOX is included in our analyses as a H₂O₂ producer, in accordance with the BRENDA annotation of the enzyme (Table 3). Further analyses of the detected NOX isoforms might identify whether they are isoforms that produce O₂^•−. Sequences that are similar to Glutathione Reductase (GR) have been documented to produce enzymes that produce extracellular O₂^•− in the diatom Thalassiosira oceanica [139]. We found sequences annotated as GR across all phytoplankton genomes (Data not visualized), which likely include genes encoding enzymes producing O₂^•−. In any case, we do not expect phytoplankton to differentially allocate a changing fraction of their total gene content to O₂^•− production with increasing cell size, as O₂^•− is weakly membrane diffusible. Phytoplankton may need to maintain working extracellular concentrations of O₂^•−, since decreasing the extracellular concentration of O₂^•− can hinder cell growth [48]. [48] further explains that the downregulation of Superoxide Dismutase (SOD, EC:1.15.1.1) genes at peak light levels by Prochlorococcus [140] would allow Prochlorococcus to maintain ‘working levels’ of extracellular O₂^•−. Beyond putative enzymatically mediated production of O₂^•−, non-enzymatic processes associated with cells can also produce O₂^•−. Notably, O₂^•− is released to variable extents from side-reactions of electron transport [38,141,142] particularly under stress conditions.

Given that the O₂^•− is poorly diffusible across membranes, intracellularly produced O₂^•− has to be scavenged to limit detrimental reactions of O₂^•− [143]. As a result, cells universally maintain the genomic capacity to scavenge O₂^•−. All prokaryotic (Data not visualized) and eukaryotic (Fig 17) phytoplankton analyzed, with the exception of a single transcriptome from Micromonas polaris, have genes annotated as encoding the ubiquitous O₂^•− scavenging enzyme SOD. Genes annotated as encoding the enzyme Superoxide Oxidase (SOO, EC:1.10.3.17) were present in a few diatom species (Leptocylindrus danicus, Chaetoceros curvicetus and Thalassiosira minuscula CCMP1093) and prokaryotes (Crocosphaera spp.). Genes encoding the enzyme Superoxide Reductase (SOR, EC:1.15.1.2) were not detected in prokaryotes, but were detected in some diatoms (Pseudo-nitzschia fradulenta WWA7 and Seminavis robusta D6), and in the haptophyte Pleurochrysis carterae CCMP456.

The absence of transcripts encoding SOD from the Micromonas polaris transcriptome is likely due to low expression of SOD at the time that the mRNA was harvested for sequence analyses. Given that the O₂^•− is not membrane diffusible, intracellularly produced O₂^•− would have to be scavenged or would react with other cell components. As a result, organisms that do not have the ability to scavenge O₂^•− would have reduced fitness and so marine phytoplankton have not lost the genomic capacity to scavenge O₂^•−. To our knowledge, our results are the first detections of the occurences of genes encoding SOO and SOR in marine phytoplankton, and need confirmation by Multiple Sequence Alignment and enzyme assays, to determine whether our results stem from errors in annotation from the non-supervised grouping of orthologs (genes) by eggNOG, or indeed represent the sporadic presence of genes for SOO and SOR in the genomes of some phytoplankters. Further trends in genomic allocations to O₂^•− scavenging may emerge from the metallo-forms of SOD [144]. For example, in pilot runs with higher discrimination among metallo-forms we found that pico-prasinophytes encode Mn-SOD instead of the Fe-SOD encoded in genomes from larger green algal phytoplankters (Data not visualized).

Influence of Cell Size on Gene Counts for Enzymes Metabolizing O₂^•−

Figure 4: Comparison of log₁₀ (Total number of genes encoding O₂^•− metabolizing enzymes (‘SupOx_count’) normalized to the total number of genes present in each organism (‘GeneModels_count’)) vs. the log₁₀ (median cell radius in µm (‘log_Radius_um’)). Poisson (solid line) or Quasi-Poisson (dashed line) regressions fitted to data ± Standard Error (dotted line). Regressions were run with (black line) or without (blue line) ‘Colony’ and ‘Flagella’ as co-variates. Selected prokaryote genomes are presented for comparison, but excluded from the presented regressions. Symbol color corresponds to taxon lineage (‘Phylum’).

With increasing cell radius, eukaryotic phytoplankton have a smaller fraction of their total genes encoding scavenging of O₂^•− (Fig 4, Blue line, Slope = -2.1×10^-1 ± 7.1×10^-2, p-value = 4.2×10^-3, pseudo R² = 0.0870217). The negative slope does not support our Hypothesis 1 that phytoplankton do not differentially allocate a changing fraction of their total gene content to O₂^•− production nor scavenging with increasing cell size. Including ‘Flagella’ and ‘Colony’ as co-variates in the regression results, however, in a slope that is not statistically different from zero (Fig 4, Black line, Slope = -6.7×10^-2 ± 6.8×10^-2, p-value = 3.3×10^-1, pseudo R² = 0.078205), driven by the influence of ‘Flagella’ (p-value = 3.7×10^-2) but not ‘Colony’ (p-value = 8.6×10^-1). Including data from selected prokaryotic phytoplankton did not qualitatively alter these results (Data not shown). O₂^•− metabolism in phytoplankton appears to be mediated by a nearly fixed set of core genes that do not change with increasing gene count, thus the fractional gene allocation to O₂^•− decreases as cell radius, and the co-varying total gene count increases. Gene dosage does not emerge as a factor in phytoplankton O₂^•− metabolism.

Influences of Flagella, Colony Formation and Cell Shape on Gene Counts for Enzymes Metabolizing O₂^•−

Figure 5: Comparison of total number of genes encoding O₂^•− scavenging enzymes (‘SupOx_count’) normalized to the total number of genes present in each organism (‘GeneModels_count’)) vs. the presence or absence of flagella in the organism. Symbol color corresponds to taxon lineage (‘Phylum’). Notch spans ± standard error of the median. Box spans median ± 1 quartile of the data. Whiskers span the range excluding outliers in the data. Citations for data sources can be found in Supplementary Table S3.

Consistent with the significant influence of flagella on the regressions vs. median cell radius (Fig 4), flagellated phytoplankton, irrespective of size, have a smaller proportion of their total gene content encoding O₂^•− scavenging (Fig 5, p-value = 4.3×10^-3), than do non-flagellated phytoplankton. This suggests that cellular motility contributes to phytoplankton homeostasis of O₂^•−, possibly by supporting escape from localized pockets of O₂^•−.

SupOxColonyPlot <- knitr::include_graphics(file.path(Figures,"SupOxColonyPlot.png"))

# SupOxColonyPlot <- knitr::include_graphics(file.path(Figures,"SupOxColonyPlot.png"))

Setting aside any influence of cell size, colony and non-colony forming phytoplankton do not significantly differ in the fraction of their total gene content encoding O₂^•− scavenging (p-value = 8.1×10^-1) (Data not visualized), consistent with limited membrane permeability for O₂^•− and thus limited colony level interactions in O₂^•− metabolism.

Pennate and centric diatoms have similar fractions of their genomes encoding O₂^•− scavenging (p-value = 9.7×10^-1) (Data not visualized). Our results support our hypothesis that differential diffusional exchange across diatoms of different shape does not influence the fraction of total gene content that encodes O₂^•− scavenging enzymes, because O₂^•− diffusion is limited by the cell membrane irrespective of cell shape (Hypothesis 1). Differences between genomic patterns of pennate and centric diatoms may arise when comparing metallo-forms of SOD, noting that [145] found that pennate diatoms transcribe Cu/Zn-SOD but not Fe-SOD, whereas centric diatoms transcribe Fe-SOD more frequently than they transcribe Cu/Zn-SOD.

Hydrogen Peroxide

All prokaryotic (Fig 20) and eukaryotic (Fig 19) phytoplankton, with the exception of a single transcriptome from the prasinophyte Micromonas polaris, have genes encoding H₂O₂ producing enzymes, as they all carry gene(s) encoding the ubiquitous enzyme Superoxide Dismutase. Genes encoding three oxidases producing H₂O₂ are also widely distributed across phytoplankton genomes. Genes for copropophyrinogen oxidase are found across all eukaryotic and prokaryotic phytoplankton, with the exception of one transcriptome. Genes encoding thiol oxidase and acyl CoA oxidase are found in nearly all eukaryotic phytoplankton, with the exception of three transcriptomes. Genes encoding L-aspartate oxidase are found in nearly all prokaryotes, and all green algae, but are nearly absent from other eukaryotic taxa. Sarcosine oxidase is not present in small diatoms and small green algae, but is present in nearly all dinoflagellates and haptophytes. (S)-2-hydroxy-acid oxidase is found in most eukaryotic phytoplankton, but rarely in dinoflagellates.

All eukaryotic (Fig 19) and most prokaryotic phytoplankton (Fig 20), have genes encoding H₂O₂ scavenging enzymes. Some strains of Prochlorococcus and Synechococcus have lost all genomic capacity to scavenge H₂O₂, and appear to rely on co-occuring hosts for H₂O₂ scavenging [71,73,90].

The absence from catalase from most analyzed cyanobacterial genomes supports [146] who analyzed 44 different cyanobacterial genomes and found that only Nostoc punctiforme PCC73102 retained a full gene encoding catalase. In our analyses, only Synechococcus elongatus PCC11802 maintained a catalase encoding gene (Fig 20). In the greens, catalase has been lost from the smaller prasinophytes but is maintained in the larger greens (Fig 19). The loss of catalase from smaller green algae may be evidence of the Black Queen Hypothesis in action [90], in that H₂O₂ can passively diffuse out of the smaller green algae but diffuses less out of larger green algae. Loss of function mutations in catalase encoding genes in small algae are therefore less deleterious than they would be to large green algae. Catalase, with a K_M of ~220 mM, may be poorly retained because the cells maintain some genomic capacity to scavenge H₂O₂ using the enzymes ascorbate peroxidase, glutathione peroxidase and Cytochrome C peroxidase (Fig 19), with K_M in the low µM range [146].

Our results support an earlier suggestion that increased genomic capacity for H₂O₂ scavenging in Synechococcus compared to Prochlorococcus is a result of the larger size in Synechococcus compared to Prochlorococcus [71] (Fig 20). It is however important to note the vast differences between prokaryotic and eukaryotic phytoplankton, with most eukaryotic phytoplankton, irrespective of lineage, maintaining the genomic capacity to produce ascorbate peroxidase, glutathione peroxidase and Cytochrome C peroxidase (Fig 19). Peroxidases are often involved in pathways beyond simple ROS scavenging, including the Halliwell-Asada cycle for ascorbate peroxidase [147]. Ostreococcus, the smallest prasinophyte has a radius of 0.5 µm, comparable to that of the prokaryote Synechococcus (Table 4), and would therefore share a similar short diffusion path length. Nevertheless Ostreococcus, in common with other eukaryotes, retains genomic capacities to produce ascorbate peroxidase, glutathione peroxidase and Cytochrome C peroxidase, which may thus reflect the cost of being eukaryotic (Fig 19).

Influence of Cell Size on Gene Counts for Enzymes Metabolizing H₂O₂

Figure 6: Comparison of log₁₀ (Total number of genes encoding H₂O₂ metabolizing enzymes (‘HyPe_count’) normalized to the total number of genes present in each organism (‘GeneModels_count’)) vs. the log₁₀ (median cell radius in µm (‘log_Radius_um’)). Poisson (solid line) or Quasi-Poisson (dashed line) regressions fitted to data ± Standard Error (dotted line). Regressions were run with (black line) or without (blue line) ‘Colony’ and ‘Flagella’ as co-variates. Selected prokaryote genomes are presented for comparison, but excluded from the presented regressions. Symbol color corresponds to taxon lineage (‘Phylum’). Citations for data sources are in Supplementary Table S3.

With increasing cell radius, eukaryotic phytoplankton have a smaller fraction of their total genes that encode the production of H₂O₂ (Fig 6, Blue line, Slope = -3.4×10^-1 ± 5×10^-2, p-value = 9.6×10^-10, pseudo R² = 0.3374895). Including ‘Flagella’ and ‘Colony’ as co-variates did not influence the negative slope of the fraction of total genes encoding H₂O₂ production with increasing median cell radius (Black line, ‘Flagella’ p-value = 8.4×10^-1, ‘Colony’ p-value = 4.7×10^-1). Including data from selected prokaryotic phytoplankton also did not qualitatively alter these results (Data not shown). The pattern of a smaller fraction of total genes for H₂O₂ production with increasing cell radius supports our Hypothesis 2 that larger phytoplankton counter decreasing diffusional loss of H₂O₂ out of cells by having lower genomic capacity for H₂O₂ production, while losses of genes encoding H₂O₂ producing enzymes are more costly to small phytoplankton (Fig 6). [7] found that a major influence upon the capacity for production of H₂O₂ is whether or not the organism can form blooms, with bloom forming species producing more H₂O₂. The ability to form blooms was not analyzed in our data as we did not find systematic information on potentials for bloom formation across taxa.

With increasing cell radius, eukaryotic phytoplankton also have a smaller fraction of their total genes that encode the capacity to scavenge H₂O₂ (Fig 6, Blue line, Slope = -3.2×10^-1 ± 5.6×10^-2, p-value = 1.4×10^-7, pseudo R² = 0.2628809). Including ‘Flagella’ and ‘Colony’ as co-variates did not influence the negative slope of the fraction of total genes encoding H₂O₂ scavenging with increasing median cell radius (Fig 6, Black line, ‘Flagella’ p-value = 4.1×10^-1, ‘Colony’ p-value = 1.6×10^-1). Including data from selected prokaryotic phytoplankton also did not qualitatively alter these results (Data not shown). A parallel analysis focusing only on small phytoplankton such as pico-cyanobacteria and pico-prasinophytes might yield different results as more genomes are sequenced, especially considering that [148] found that H₂O₂ added to seawater at a concentration of 1.6 mg L^-1 did not affect cells with a radius larger than 1 to 1.5 μm, but differentially harmed the picoprasinophyte Micromonas pusilla.

Noting that the fraction of total genes allocated to both H₂O₂ production and scavenging decrease with increasing median cell radius, we found that the fraction of total genes that encode production of H₂O₂ decreases proportionally more with increasing cell radius than does the fraction of total genes that encode scavenging of H₂O₂ (4.6×10^-50). The difference in slopes supports our Hypothesis 2 that large phytoplankton counter decreasing diffusional loss of H₂O₂ out of cells by having lower genomic capacity for H₂O₂ production relative to H₂O₂ scavenging. Because median cell radius co-varied with Taxa, we generally excluded Taxa as a co-variate from our regressions, in order to focus on any cross-taxon patterns driven by changing median cell radius. Nevertheless, representatives of the Ochrophyte Phylum alone spanned more than an order of magnitude in median cell radius. We therefore tested whether the log₁₀(total number of genes encoding the metabolism of O₂^•−, H₂O₂ or ^•NO) varied with the log₁₀ (median cell radius) across the Ochrophytes alone (Fig 16). We found that across Ochrophytes, the fraction of total genes encoding the production of H₂O₂ decreased with increasing cell radius (Slope = -1.6×10^-1 ± 9.4×10^-2), although the p-value for the regression was only 1×10^-1. This marginal decrease in the total number of genes encoding H₂O₂ production with increasing median cell radius in Ochrophytes again tends to support our Hypothesis 2, with data from within a single phylum to limit confounding influences of diverse evolutionary histories and cell biologies upon patterns.

Influences of Flagella, Colony Formation and Cell Shape on Gene Counts for Enzymes Metabolizing H₂O₂

Figure 7: Comparison of total number of genes encoding H₂O₂ metabolizing enzymes (‘HyPe_count’) normalized to the total number of genes present in each organism (‘GeneModels_count’) vs. the presence or absence of flagella in the organism. Symbol color corresponds to taxon lineage (‘Phylum’). Notch spans ± standard error of the median. Box spans median ± 1 quartile of the data. Whiskers span the range excluding outliers in the data. Citations for data sources can be found in Supplementary Table S3.

Setting aside influences of median cell radius, non-flagellated vs. flagellated phytoplankton exhibit no statistically significant difference in the fraction of their total genes encoding the production of H₂O₂ (p-value = 5.9×10^-2), whereas non-flagellated phytoplankton have a significantly larger proportion of their total gene content encoding H₂O₂ scavenging (p-value = 6.9×10^-3), than do flagellated phytoplankton (Fig 7). Thus, presence of flagella may contribute to the maintenance of H₂O₂ homeostasis across eukaryotic phytoplankton, but this potential influence is obscured by the range of cell sizes across eukaryotic phytoplankton when flagella are included as a co-variate in size regressions.

Figure 8: Comparison of total number of genes encoding H₂O₂ metabolizing enzymes (‘HyPe_count’) normalized to the total number of genes present in each organism (‘GeneModels_count’) vs. the ability of the organism to form colonies. Symbol color corresponds to taxon lineage (‘Phylum’). Notch spans ± standard error of the median. Box spans median ± 1 quartile of the data. Whiskers span the range excluding outliers in the data. Citations for data sources can be found in Supplementary Table S3.

Setting aside cell size influences, non-colony forming phytoplankton have a smaller proportion of their total gene content encoding both H₂O₂ production (p-value = 3.2×10^-2), and also H₂O₂ scavenging (Fig 8, p-value = 1.7×10^-2), than do colony forming phytoplankton. Looking at proportional change, we found that the decrease in the fraction of total genes encoding H₂O₂ production between non-colony and colony forming phytoplankton is smaller (-24.71%), than the decrease in the fraction of total genes encoding H₂O₂ scavenging (-27.79%). Colony forming phytoplankton may have more active H₂O₂ metabolism with a particular emphasis on H₂O₂ scavenging, consistent with stronger H₂O₂ exchange among closely spaced cells within a colony (Hypothesis 4) [75].

Pennate and centric diatoms do not show statistically significant differences in the fraction of their total gene content encoding the production (p-value = 1.9×10^-1) nor the scavenging of H₂O₂ (p-value = 9.6×10^-2). This result does not support our Hypothesis 3 that pennates have more genes encoding H₂O₂ producing enzymes due to their higher surface area to volume ratio (Data not visualized).

Nitric Oxide

In the genomes and transcriptomes that we analysed, Nitric Oxide Synthase (NOS, EC:1.14.13.39) was the most frequently occurring ^•NO producing enzyme encoded (Fig 21), but was not encoded, or at least not annotated, among prokaryotic phytoplankton (Data not visualized).

Nitric Oxide Dioxygenase (NOD, EC:1.14.12.17) was the most frequently occurring of the ^•NO scavenging enzymes (Fig 21). NOD sequences were identified in some eukaryotes, but were either not annotated, or not present in Prochlorococcus, most green algae and most centric diatoms. A NOS-like sequence has recently been identified in Synechococcus, that also has Nitric Oxide Dioxygenase-like function [149], and which might mediate NOD activity in some strains lacking annotated NOD sequences.

Influence of Cell Size on Gene Counts for Enzymes Metabolizing ^•NO

Figure 9: Comparison of log₁₀ (Total number of genes encoding ^•NO metabolizing enzymes (‘NitOx_count’) normalized to the total number of genes present in each organism (‘GeneModels_count’)) vs. the log₁₀ (median cell radius in µm (‘log_Radius_um’)). Poisson (solid line) or Quasi-Poisson (dashed line) regressions fitted to data ± Standard Error (dotted line). Regressions were run with (black line) or without (blue line) ‘Colony’ and ‘Flagella’ as co-variates. Selected prokaryote genomes are presented for comparison, but excluded from the presented regressions. Symbol color corresponds to taxon lineage (‘Phylum’).

With increasing cell radius eukaryotic phytoplankton do not vary in the fraction of total genes encoding the capacity to produce ^•NO (Fig 9, Blue line, Slope = -2.5×10^-1 ± 1.7×10^-1, p-value = 1.5×10^-1, pseudo R² = 0.0239463). Including prokaryotes in the regression in Fig 9 does not substantially alter the interpretation (Data not visualized). We re-ran the quasipoisson, excluding those organisms that completely lack genes encoding enzymes for ^•NO production (NitOx_count = 0, points along the x-axis), which resulted in a decreasing slope with increasing cell radius. Thus those phytoplankton with any detected capacity to produce ^•NO indeed have a smaller fraction of their total genes encoding ^•NO production with increasing radius (Fig 9, Blue line, Slope = -3.7×10^-1 ± 1.1×10^-1, p-value = 8.6×10^-4, pseudo R² = 0.133218). Including ‘Flagella’ and ‘Colony’ as co-factors to the regression that solely looks at organisms with the genomic capacity to produce ^•NO resulted in a slope that is no longer significantly different from zero (Fig 9, Black line, Slope = -2.5×10^-1 ± 1.4×10^-1, p-value = 7×10^-2, pseudo R² = 0.0310994), driven by the influence of ‘Flagella’ (p-value = 1.4×10^-4), but not ‘Colony’ (p-value = 1.8×10^-1).

With increasing cell radius, eukaryotic phytoplankton do not vary in the fraction of their total genes encoding the capacity to scavenge ^•NO, quasipoisson regression slope not significantly different from zero (Fig 9, Blue line, Slope = 1.3×10^-1 ± 1.8×10^-1, p-value = 4.7×10^-1, pseudo R² = 0.0372253). Including prokaryotes in the quasipoisson regression from Fig 9 does not alter the interpretation, as the slope is still not significantly different from zero. We re-ran the quasipoisson, excluding those organisms that completely lack genes encoding enzymes for ^•NO scavenging (NitOx_count = 0, points along the x-axis), and found the exclusion did not alter the slope of the fraction of total genes encoding ^•NO scavenging with increasing radius.

Non-enzymatic paths contribute to intracellular and extracellular ^•NO production [150], and may explain the absences of genes encoding ^•NO production from some genomes across taxonomic lineages. Alternately, ^•NO homeostasis may be achieved in some lineages by regulating the active cellular uptake and release of intracellular ^•NO, as has been recently demonstrated in humans [151]. Although NOD sequences have only been identified from phytoplankton through metatranscriptomic analyses, in diatoms, haptophytes and dinoflagellates [152], there is limited understanding as to what may contribute to the active removal of ^•NO, and the lack of ^•NO scavenging genes across multiple phytoplankters. More research is needed on possible contributions of NOD to the active removal of ^•NO, as well as the NOS sequences detected in Synechococcus that also display NOD-like activity [149]. Perhaps the low toxicity of ^•NO does not warrant the active removal of ^•NO as long as the concentration does not exceed the toxic threshold. This explanation is plausible given that Platymonas helgolandica, Platymonas subcordiformis, Skeletonema costatum, Gymnodinium sp., and Prorocentrum donghaiense showed optimum growth in the presence of ^•NO concentrations between 10^-9 and 10^-6 mol L^-1 [153], which are higher than the concentrations found in the ocean (Table 1).

Influences of Flagella, Colony Formation and Cell Shape on Gene Counts for Enzymes Metabolizing ^•NO

NitOxFlagella <- MergedData %>% 
  filter(Taxa != "Prokaryote", 
         NitOx %in% c("Production", "Scavenging")) %>%
  select(FileName, Genus, species, Strain, Name, Ome, Taxa, Rad1_um, Rad2_um, Rad3_um, Flagella, GenomeSize_mbp, GeneModels_count, Latitude, Longitude, Marine, HyPe, PennateCentric, SA_um2, Volume_um3, SAVol_um, Radius_um, log_Radius_um, log_GenomeSize_mbp, log_GeneModels_count, abs_Latitude, log_Volume_um3, log_SA_um2, log_SAVol_um, ROSGene_count, ECNumber, EnzymeName, ColonySpecies, NitOx_count, NitOx) %>%
  unique() %>%
  mutate(NitOx_countL = NitOx_count %>% as.logical() %>% as.numeric(),
         FlagellaL = ifelse(Flagella == "yes", 1, 0)) %>%
  select(FileName, NitOx_count, NitOx_countL, Flagella, FlagellaL,NitOx) %>%
  # filter(GeneModels_count != 0) %>% #This is because of introducing exposure
  nest(data = -c(NitOx)) %>%
  mutate(fit_b_offset = map(data, possibly(~glm(.$NitOx_countL ~ .$FlagellaL, data = ., family = binomial(link = "logit")), otherwise = NULL)),
                    param_b_offset = map(fit_b_offset, tidy),
                    pred_b_offset = map(fit_b_offset, augment))

Setting aside the influence of cell size, non-flagellated and flagellated phytoplankton do not show statistically significant differences in the fractions of total gene content encoding ^•NO production (p-value = 6.3×10^-1) nor ^•NO scavenging (p-value = 8.9×10^-1) (Data not visualized), suggesting ^•NO does not have a generalized interaction with flagella across eukaryotic phytoplankton groups.

Presence absence = non-flagellated phytoplankton have 0.4655172 probability of having a nitric oxide producing gene as opposed to 0.6222222 in flagellated phytoplankton (p-value = 4.3×10^-4. Non flagellated phytoplankton also have a 0.4482759 probability of having a nitric oxide scavenging gene, as opposed to 0.5555556 in flagellated phytoplankton (p-value = 3.1×10^-2.

XXX

NitOxColonyPlot <- knitr::include_graphics(file.path(Figures,"NitOxColonyPlot.png"))

Comparing non-colony to colony forming phytoplankton does not show a statistically significant difference in the fraction of total gene content encoding ^•NO production (p-value = 7.7×10^-1) nor ^•NO scavenging (p-value = 2.7×10^-1) (Data not visualized), suggesting ^•NO metabolism does not have a generalized role in colony formation across eukaryotic phytoplankton groups.

Presence absence = non-colony forming phytoplankton have 0.5882353 probability of having a nitric oxide producing gene as opposed to 0.5 in colony forming phytoplankton (p-value = 8.5×10^-2. Non colony forming phytoplankton also have a 0.372549 probability of having a nitric oxide scavenging gene, as opposed to 0.5 in colony forming phytoplankton (p-value = 2.5×10^-2.

Figure 10: Comparison of total number of genes encoding ^•NO metabolizing enzymes (‘NitOx_count’) normalized to the total number of genes present in each diatom (‘GeneModels_count’) vs. the growth form of the diatom (‘PennateCentric’). Symbol color corresponds to taxon lineage (‘Phylum’). Notch spans ± standard error of the median. Box spans median ± 1 quartile of the data. Whiskers span the range excluding outliers in the data. Citations for data sources can be found in Supplementary Table S3.

Most centric diatoms carry genes annotated as encoding ^•NO producing enzymes, whereas most pennate diatoms do not (p-value = 6.2×10^-3). In contrast, most centric diatoms lack genes annotated as encoding ^•NO scavenging enzymes, whereas most pennate diatoms carry those genes (p-value = 3.8×10^-5) (Fig 10).

The larger fractional gene allocation to ^•NO production, and smaller fraction of genes that encode ^•NO scavenging enzymes, in centric diatoms (Fig 10) counters our hypothesis that diffusion from pennate diatoms would drive gene allocations in favor of ^•NO production (Hypothesis 3). Given the strong contrast in annotated ^•NO metabolism genes, it is likely that ^•NO has regulatory or signaling roles that vary systematically between pennate and centric diatoms, outside any diffusional influences. For example, ^•NO inhibits diatom adhesion to substrate [81,154]. Pennates are more likely to grow adhered in biofilms [155], which may explain the striking differences in total gene allocation to ^•NO production and scavenging. Alternately, [156] identified putative NOS sequences in the transcriptomes of three Pennate Diatom species (Pseudo-nitzschia arenysensis, Pseudo-nitzschia delicatissima and Pseudo-nitzschia multistriata), so it is possible the apparent lack of ^•NO producing sequences in pennates is due to errors in the unsupervised annotations from eggNOG.

Presence absence = centric diatoms have 0.5238095 probability of having a nitric oxide producing gene as opposed to a 0.125 probability in pennate diatoms (p-value = 1.7×10^-7. Centric diatoms also have a 0.1904762 probability of having a nitric oxide scavenging gene, as opposed to a 0.875 probability in colony forming phytoplankton (p-value = 4.7×10^-13.

Summary

The differential reactivities, diffusion distances, diffusibilities across cell membranes, and roles in cell signaling of H₂O₂, O₂^•− and ^•NO (Table 1) influence genomic allocation patterns for the production and scavenging of these three distinct ROS.

O₂^•− has high reactivity, short intracellular and extracellular lifetimes and limited cell membrane crossing. We did not find genes specifically encoding O₂^•− production in eukaryotic phytoplankton genomes. As expected, genes encoding O₂^•− scavenging were ubiquitous, but the fractional gene allocation to O₂^•− scavenging decreases as cell radius, and the co-varying total gene count increases, consistent with a nearly fixed set of core genes scavenging O₂^•− that do not change with increasing gene count.

H₂O₂ has lower reactivity, longer intracellular and extracellular lifetimes and readily crosses cell membranes. Across eukaryotic phytoplankton, the fraction of the total genes encoding H₂O₂ producing enzymes decreases with increasing cell radius, consistent with maintenance of ROS homeostasis in the face of slower diffusional losses from larger cells. The fraction of the total genes encoding H₂O₂ scavenging enzymes also decreases with increasing cell radius, but with a slope smaller than that for H₂O₂ producing enzymes. Presence of flagella and colony formation appear to influence H₂O₂ metabolism, supporting interactions between growth form and H₂O₂ homeostasis.

^•NO has low reactivity, long intracellular and extracellular lifetimes and readily crosses cell membranes. Neither the fraction of the total genes for ^•NO production nor for scavenging changed significantly with increasing cell radius, consistent with relatively low cytotoxicity and roles of ^•NO in taxonomically diverse regulatory systems. Pennate diatoms frequently lack genes annotated as encoding ^•NO producing enzymes, whereas centric diatoms frequently lack genes annotated as encoding ^•NO scavenging enzymes. This finding is not explicable by differential diffusional losses of ^•NO, but may reflect distinct roles of ^•NO in the regulatory systems of diatom lineages.

Funding Information

NMO was supported by the Mount Allison University Rice Memorial Graduate Fellowship and a New Brunswick Innovation Foundation STEM Graduate Award. KF was supported by NSERC Indigenous Undergraduate Summer Research Award and the MITACS GlobalLink internship. BB was supported by the Canada Research Chair in Phytoplankton Ecophysiology fund. DAC was supported by the Canada Research Chair in Phytoplankton Ecophysiology and by the Microbiology Institute of the Czech Academy of Science through project CZ.02.2.69/0.0/0.0/16_027/0007990 of the European Union Researcher Mobility program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Open Data Statement

Code, genes annotated for ROS metabolism (MergedData.csv), MetaData.csv and DataDictionary.csv are stored on https://github.com/NaamanOmar/ROS_bioinfo/tree/master/ROSGenomicPatternsAcrossMarinePhytoplankton.

Annotations of all genes from genomes or transcriptomes of organisms used in this study, MetaData.csv and DataDictionary.csv are stored on DRYAD (DOI pending) to facilitate reuse for other purposes.

Supplementary Materials

Supplementary Figures

Figure 11: Violin plot presenting the range of log₁₀ of the median cell radius in µm (‘log_Radius_um’) for each taxonomic lineage (‘Phylum’). Point colour corresponds to the source of the data, whether Genome or Transcriptome (‘Ome’). Violin width indicates the fraction of all datapoints occuring at a cell radius (‘log_Radius_um’) within a phylum. Citations for data sources are in Supplementary Table S3.

Figure 12: Longitude and Latitude of isolation of analyzed organisms, overlaid on a world map Point colour corresponds to the taxonomic lineage (‘Phylum’). Ocean colour corresponds to depth Citations for data sources are in Supplementary Table S3. Data used to generate world map produced from the ‘ggOceanMaps’ R package [157]

Figure 13: Comparison of paired counts of particular genes encoding ROS Production or Scavenging from manual and automatic annotations taken from the same organism. Data was drawn from a subset of genomes and transcriptomes which were both manually and automatically annotated. Colour corresponds to the ‘Gene’ Points are jittered to avoid overlapping, resulting in blocks around frequently occuring counts. Dashed line is placed at 1:1 where Manual and Automated counts would be equal. Citations for data sources in Supplemental Data Table S4.

Figure 14: Histogram of occurrences of number of total genes, in a genome or transcriptome, (y axis) that code for the production of enzymes that produce or scavenge H₂O₂, O₂^•− or ^•NO in vivo. Symbol color corresponds to taxon lineage (‘Taxa’)

Figure 15: Comparison of paired counts of particular genes encoding ROS Production or Scavenging from the genome (‘ROSGene_count.g’) or transcriptome (‘ROSGene_count.t’) taken from the same organism. Data was drawn from a subset of analyzed organisms for which both genome and transcriptome were available. Colour corresponds to the taxonomic lineage (‘Phylum’) Points are jittered to avoid overlapping, resulting in blocks around frequently occuring counts. Dashed line is at 1:1 where ‘ROSGene_count.g’ and ‘ROSGene_count.t’ would be equal. Citations for data sources are in Supplementary Table S3.

Figure 16: Comparison of log₁₀ (Total number of genes encoding H₂O₂, O₂^•− or ^•NO metabolizing enzymes normalized to the total number of genes present in each Ochrophyte) vs. the log₁₀( median cell radius in µm). Poisson (solid line) or Quasi-Poisson (dashed line) regressions fitted to data ± Standard Error (dotted line). Regressions were run without (blue line) ‘Colony’ and ‘Flagella’ as co-variates. Citations for data sources are in Supplementary Table S3.

Figure 17: Summary of O₂^•− scavenging enzymes encoded within genomes and transcriptomes of eukaryotic phytoplankton analyzedTaxa are ordered from top to bottom along the left according to increasing median cell diameter within each taxonomic lineage. Symbol colour corresponds to taxonomic lineages (‘Taxa’).Filled data points indicate that the data obtained from that organism was sourced from a genome, and unfilled data points were sourced from a transcriptome. The size of the symbol increases with the number of members of each enzyme found within each genome or transcriptome. Symbol absence means no sequences known to encode the enzyme family of interest were found in the target genome or transcriptome.

SupOxFlagRiboPlot <- knitr::include_graphics(file.path(Figures,"SupOxFlagRiboPlot.png"))

Figure 18: Comparison of total number of genes encoding O₂^•− scavenging enzymes (‘SupOx_count’) normalized to the total number of genes present in each organism (‘GeneModels_count’)) vs. the presence or absence of flagella in the organism. Symbol color corresponds to taxon lineage (‘Phylum’). Notch spans ± standard error of the median. Box spans median ± 1 quartile of the data. Whiskers span the range excluding outliers in the data. Citations for data sources can be found in Supplementary Table S3.

Figure 19: Summary of H₂O₂ metabolizing enzymes encoded within genomes and transcriptomes of eukaryotic phytoplankton analyzed, faceted by whether the enzymes Produce or Scavenge H₂O₂. Taxa are ordered from top to bottom along the left according to increasing median cell diameter within each taxonomic lineage. Symbol colour corresponds to taxonomic lineages (‘Taxa’). Filled data points indicate that the data obtained from that organism was sourced from a genome, and unfilled data points were sourced from a transcriptome. The size of the symbol increases with the number of members of each enzyme found within each genome or transcriptome. Symbol absence means no sequences known to encode the enzyme family of interest were found in the target genome or transcriptome.

Figure 20: Summary of H₂O₂ metabolizing enzymes encoded within genomes of prokaryotic phytoplankton analyzed, faceted by whether the enzymes Produce or Scavenge H₂O₂. Taxa are ordered from top to bottom along the left according to increasing median cell diameter within each taxonomic lineage. Symbol colour corresponds to the genus of the prokaryote.Filled data points indicate that the data obtained from that organism was sourced from a genome. The size of the symbol increases with the number of members of each enzyme found within each genome or transcriptome. Symbol absence means no sequences known to encode the enzyme family of interest were found in the target genome or transcriptome.

HyPeColonyRiboPlot <- knitr::include_graphics(file.path(Figures,"HyPeColonyRiboPlot.png"))

Figure 21: Summary of ^•NO metabolizing enzymes encoded within genomes and transcriptomes of eukaryotic phytoplankton analyzed, faceted by whether the enzymes Produce or Scavenge ^•NO. Taxa are ordered from top to bottom along the left according to increasing median cell diameter within each taxonomic lineage. Symbol colour corresponds to taxonomic lineages (‘Taxa’). Filled data points indicate that the data obtained from that organism was sourced from a genome, and unfilled data points were sourced from a transcriptome. The size of the symbol increases with the number of members of each enzyme found within each genome or transcriptome. Symbol absence means no sequences known to encode the enzyme family of interest were found in the target genome or transcriptome.

Supplementary Tables

Table 2: Variable names, definitions, units, and first location of occurence in code, used for our data.

Variable	Units	Definition
FileName		Name of source genome or transcriptome file composed of three components - Name, Nucleic acid and Genome or Transcriptome, separated by dashes
EnzymeName		Name of ROS producing or scavenging enzyme
ECNumber		Enzyme Commission Number of enzyme
HyPe		Indicates whether the enzyme Produces or Scavenges Hydrogen Peroxide
SupOx		Indicates whether the enzyme Produces or Scavenges Superoxide
NitOx		Indicates whether the enzyme Produces or Scavenges Nitric Oxide
Genus		Genus of the organism
species		Species of the organism
Strain		Strain of the organism
Ome		Genome or Transcriptome
Taxa		Taxonomic group that the organism falls in, typically class, phyla or superphyla
Rad1_um	µm	Smallest median radius (in µm) along all three axes
Rad2_um	µm	Second largest median radius (in µm) along all three axes
Rad3_um	µm	Largest median radius (in µm) along all three axes
Flagella		Refers to whether or not the organism has flagella
GenomeSize_mbp	mbp	Size of the genome in megabasepairs
GeneModels_count	count	Total number of genes in genome
Latitude	°	Source latitude from which the organism was sampled in degrees
Longitude	°	Source longitude from which the organism was sampled in degrees
Marine		States whether the organism is Marine or not
PennateCentric		Solely for Diatoms, indicates whether the Diatom is a Pennate or a Centric Diatom
ColonySpecies		Indicates whether an organism can form colonies or not
KO		Kegg Orthology Number
HyPe_PriSec		If the Enzyme Produces or Scavenges Hydrogen Peroxide, HyPePriSec indicates whether Hydrogen Peroxide is a Primary or Secondary product or substrate
HyPe_PriSec_citekey		Citation for HyPe
NitOx_PriSec		If the Enzyme Produces or Scavenges Nitric Oxide, NitOxPriSec indicates whether Nitric Oxide is a Primary or Secondary product or substrate
NitOx_PriSec_citekey		Citation for NitOx_PriSec
SupOx_PriSec		If the Enzyme Produces or Scavenges Superoxide, SupOxPriSec indicates whether Superoxide is a Primary or Secondary product or substrate
SupOx_PriSec_citekey		Citation for SupOx_PriSec
Reaction		Reaction of the enzyme to produce or scavenge ROS; if multiple reactions are present, they are separated by “;”
Reaction_citation		Citation for Reaction
ECTreeL1		First Level Description of EC Tree
ECTreeL2		Second Level Description of EC Tree
ECTreeL3		Third Level Description of EC Tree
ProdAndScav		An enzyme that is annotated as both producing and scavenging the substrate
RemoveEnzyme		Remove an enzyme as per methods
Notes		Notes
query_name		query sequence name
seed_eggNOG_ortholog		best protein match in eggNOG
seed_ortholog_evalue		best protein match (e-value)
seed_ortholog_score		best protein match (bit-score)
eggNOG OGs		a comma-separated, clade depth-sorted (broadest to narrowest), list of Orthologous Groups (OGs) identified for this query. Note that each OG is represented in the following format: OG@tax_id|tax_name
narr_og_name		OG@tax_id|tax_name for the narrowest OG found for this query.
narr_og_cat		COG category corresponding to narr_og_name
narr_og_desc		Description corresponding to narr_og_name
best_og_name		OG@tax_id|tax_name for the OG chosen based on –tax_scope.
best_og_cat		COG category corresponding to best_og_name
best_og_desc		Description corresponding to best_og_name
Preferred_name		EGGNOG annotation of enzyme name
GOs		Gene Ontology
KEGG_ko		Kegg Orthology Number
KEGG_Pathway		KEGG Pathway
KEGG_Module		KEGG Module
KEGG_Reaction		KEGG Reaction
KEGG_rclass		KEGG rclass
BRITE		Hierarchical classification systems capturing functional hierarchies of various biological objects
KEGG_TC		KEGG Transporter Classification
CAZy		Carbohydrate-Active enZYmes
BiGG_Reaction		Biochemical Genetic and Genomic
PFAMs		Protein Families
ROSGene_count	count	Count of genes encoding an enzyme by EC number
TotalDetectedEnzymes	count	Total count of detected enzyme encoding genes in the genome
SA_um2	µm2	Surface area in µm2
Volume_um3	µm3	Volume in µm3
SAVol_um	µm-1	Surface area to Volume ratio in µm-1
Radius_um	µm	Smallest median radius (in µm) along all three axes
log_Radius_um	µm	log10 of Radius_µm
log_GenomeSize_mbp	mbp	log10 of GenomeSize_mbp
log_GeneModels_count	count	log10 of GeneModel_count
log_Gene_count	count	log10 of Gene_count
abs_Latitude	°	absolute of Latitude
log_Volume_um3	µm3	log10 of Volume_µm3
log_SA_um2	µm2	log10 of SA_µm2
log_SAVol_um	µm-1	log10 of SAVol_perµm
Name		Combination of Genus, species, Strain
Phylum		Taxonomic group that the organism falls in, typically class, phyla or superphyla
HyPe_count		Total count of genes encoding Production or Scavenging of HyPe
NitOx_count		Total count of genes encoding Production or Scavenging of NitOx
SupOx_count		Total count of genes encoding Production or Scavenging of SupOx
TotalROSGene_count		Total count of genes encoding Production or Scavenging of HyPe, NitOx and SupOx
TransWGenomePresent		A transcriptome that also has a genome published; these are used for quality control

Table 3: Enzyme Commission Number, Kegg Orthology Number, Enzyme Name and ROS Substrate Metabolised

ECNumber	KO	EnzymeName	SupOx	HyPe	NitOx
1.1.3.4		Glucose oxidase		Production
1.1.3.B4		Glycerol oxidase		Production
1.1.3.5	K21840	Hexose oxidase		Production
1.1.3.6	K03333	Cholesterol oxidase		Production
1.1.3.7		Aryl-Alcohol oxidase		Production
1.1.3.8	K00103	L-gulonolactone oxidase		Production
1.1.3.9	K04618	Galactose oxidase		Production
1.1.3.10	K23272	Pyranose oxidase		Production
1.1.3.11		L-sorbose oxidase		Production
1.1.3.12	K18607	Pyridoxine 4-oxidase		Production
1.1.3.13	K17066	Alcohol oxidase		Production
1.1.3.15	K00104;K11517	(S)-2-hydroxy-acid oxidase		Production
1.1.3.16	K10724	Ecdysone oxidase		Production
1.1.3.17	K17755	choline oxidase		Production
1.1.3.18		secondary-alcohol oxidase		Production
1.1.3.19		4-hydroxymandelate oxidase (decarboxylating)		Production
1.1.3.20	K17756	long-chain-alcohol oxidase		Production
1.1.3.21	K00105	glycerol-3-phosphate oxidase		Production
1.1.3.27		hydroxyphytanate oxidase		Production
1.1.3.30		polyvinyl-alcohol oxidase		Production
1.1.3.37	K00107	D-arabinono-1,4-lactone oxidase		Production
1.1.3.38	K20153	vanillyl-alcohol oxidase		Production
1.1.3.39		nucleoside oxidase (H2O2-forming)		Production
1.1.3.40		D-mannitol oxidase		Production
1.1.3.41	K00594	alditol oxidase		Production
1.1.3.42	K20550	prosolanapyrone-II oxidase		Production
1.1.3.45	K15949	aclacinomycin-N oxidase		Production
1.1.3.46	K16422	4-hydroxymandelate oxidase		Production
1.1.3.47	K16873	5-(hydroxymethyl)furfural oxidase		Production
1.1.3.48	K19714	3-deoxy-alpha-D-manno-octulosonate 8-oxidase		Production
1.1.5.13	K15736	(S)-2-hydroxyglutarate dehydrogenase		Production
1.1.98.3	K16653	decaprenylphospho-beta-D-ribofuranose 2-dehydrogenase		Production
1.1.99.B3		glucooligosaccharide oxidase		Production
1.1.99.18		cellobiose dehydrogenase (acceptor)		Production
1.2.3.1	K00157	aldehyde oxidase		Production
1.2.3.3	K00158	pyruvate oxidase		Production
1.2.3.4		oxalate oxidase		Production
1.2.3.5		glyoxylate oxidase		Production
1.2.3.7	K11817	indole-3-acetaldehyde oxidase		Production
1.2.3.9		aryl-aldehyde oxidase		Production
1.2.3.14	K09842	abscisic-aldehyde oxidase		Production
1.2.3.15	K20929	(methyl)glyoxal oxidase		Production
1.3.3.3	K00228	coproporphyrinogen oxidase		Production
1.3.3.4	K00231	protoporphyrinogen oxidase		Production
1.3.3.6	K00232	acyl-CoA oxidase		Production
1.3.3.8	K22089	tetrahydroberberine oxidase		Production
1.3.3.11	K06137	pyrroloquinoline-quinone synthase		Production
1.3.3.12		L-galactonolactone oxidase		Production
1.3.3.13	K21375	albonoursin synthase		Production
1.3.3.14	K15949	aclacinomycin-A oxidase		Production
1.3.3.16	K05897	oxazoline dehydrogenase		Production
1.3.98.1	K00226	dihydroorotate dehydrogenase (fumarate)		Production
1.4.3.1	K00272	D-aspartate oxidase		Production
1.4.3.B1	K09471	gamma-glutamylputrescine oxidase		Production
1.4.3.2	K03334	L-amino-acid oxidase		Production
1.4.3.3	K00273	D-amino-acid oxidase		Production
1.4.3.4	K00274	monoamine oxidase		Production
1.4.3.5	K00275	pyridoxal 5’-phosphate synthase		Production
1.4.3.7		D-glutamate oxidase		Production
1.4.3.8		ethanolamine oxidase		Production
1.4.3.10	K03343	putrescine oxidase		Production
1.4.3.11		L-glutamate oxidase		Production
1.4.3.12		cyclohexylamine oxidase		Production
1.4.3.13	K00277	protein-lysine 6-oxidase		Production
1.4.3.14		L-lysine oxidase		Production
1.4.3.15		D-glutamate(D-aspartate) oxidase		Production
1.4.3.16	K00278	L-aspartate oxidase		Production
1.4.3.19	K03153	glycine oxidase		Production
1.4.3.20	K17831	L-lysine 6-oxidase		Production
1.4.3.21	K00276	primary-amine oxidase		Production
1.4.3.22	K11182	diamine oxidase		Production
1.4.3.23	K19884	7-chloro-L-tryptophan oxidase		Production
1.4.3.25	K21639	L-arginine oxidase		Production
1.5.3.1	K00301;K00302;K00303;K00304;K00305	sarcosine oxidase		Production
1.5.3.4		N6-methyl-lysine oxidase		Production
1.5.3.5	K19826	(S)-6-hydroxynicotine oxidase		Production
1.5.3.6	K19890	(R)-6-hydroxynicotine oxidase		Production
1.5.3.7	K00306	L-pipecolate oxidase		Production
1.5.3.10	K00309	dimethylglycine oxidase		Production
1.5.3.12		dihydrobenzophenanthridine oxidase		Production
1.5.3.13	K00308	N1-acetylpolyamine oxidase		Production
1.5.3.14	K13366	polyamine oxidase (propane-1,3-diamine-forming)		Production
1.5.3.15		N8-acetylspermidine oxidase (propane-1		Production
1.5.3.16	K12259	spermine oxidase		Production
1.5.3.17	K13367;K17839	non-specific polyamine oxidase		Production
1.5.3.18	K17833	L-saccharopine oxidase		Production
1.5.8.4	K00315	dimethylglycine dehydrogenase		Production
1.6.3.1	K13411	NAD(P)H oxidase (H2O2-forming)		Production
1.6.3.3	K17870	NADH oxidase (H2O2-forming)		Production
1.6.3.5	K18208	renalase		Production
1.7.3.1	K19823	nitroalkane oxidase		Production
1.7.3.3	K00365	factor-independent urate hydroxylase		Production
1.8.3.1	K00387	sulfite oxidase		Production
1.8.3.2	K10758;K17783;K17891	thiol oxidase		Production
1.8.3.3		glutathione oxidase		Production
1.8.3.4	K17285	methanethiol oxidase		Production
1.8.3.5	K05906	prenylcysteine oxidase		Production
1.8.3.6	K05906	farnesylcysteine lyase		Production
1.10.3.4	K20219	o-aminophenol oxidase		Production
1.10.3.5		3-hydroxyanthranilate oxidase		Production
1.10.3.6		rifamycin-B oxidase		Production
1.11.1.1	K05910	NADH peroxidase		Production
1.13.12.9	K21795	phenylalanine 2-monooxygenase		Production
1.13.12.16	K00459	nitronate monooxygenase		Production
1.14.99.24		steroid 9alpha-monooxygenase		Production
1.14.99.66	K11450	[histone H3]-N6,N6-dimethyl-L-lysine4 FAD-dependent demethylase		Production
1.15.1.1	K00518;K04564;K04565;K16627	superoxide dismutase	Scavenging	Production
1.15.1.2	K05919	superoxide reductase	Scavenging	Production
1.16.3.2	K00522;K02217	bacterial non-heme ferritin		Production
1.17.1.4	K00087;K11177;K11178;K13479;K13481;K13482	xanthine dehydrogenase		Production
1.17.3.2		xanthine oxidase		Production
1.21.3.3	K00307	reticuline oxidase		Production
1.21.3.7	K20501	tetrahydrocannabinolic acid synthase		Production
1.21.3.8	K20502	cannabidiolic acid synthase		Production
2.1.1.148	K03465	thymidylate synthase (FAD)		Production
4.1.1.107	K01618	3,4-dihydroxyphenylacetaldehyde synthase		Production
4.1.1.108	K22327	4-hydroxyphenylacetaldehyde synthase		Production
4.1.1.109	K22328	phenylacetaldehyde synthase		Production
1.1.3.17	K17755	choline oxidase		Scavenging
1.2.3.9		aryl-aldehyde oxidase		Scavenging
1.3.98.5	K00435;K25033	hydrogen peroxide-dependent heme synthase		Scavenging
1.4.3.3	K00273	D-amino-acid oxidase		Scavenging
1.11.1.1	K05910	NADH peroxidase		Scavenging
1.11.1.B2		chloride peroxidase (vanadium-containing)		Scavenging
1.11.1.3		fatty-acid peroxidase		Scavenging
1.11.1.5	K00428	cytochrome-c peroxidase		Scavenging
1.11.1.6	K03781	catalase		Scavenging
1.11.1.7	K00430;K10788;K12550;K19511;K21201	peroxidase		Scavenging
1.11.1.8	K00431	iodide peroxidase		Scavenging
1.11.1.9	K00432	glutathione peroxidase		Scavenging
1.11.1.10	K00433;K17990	chloride peroxidase		Scavenging
1.11.1.11	K00434	L-ascorbate peroxidase		Scavenging
1.11.1.13	K20205	manganese peroxidase		Scavenging
1.11.1.14	K23515	lignin peroxidase		Scavenging
1.11.1.16		versatile peroxidase		Scavenging
1.11.1.19	K15733	dye decolorizing peroxidase		Scavenging
1.11.1.21	K03782	catalase-peroxidase		Scavenging
1.11.1.23	K12903;K22392	(S)-2-hydroxypropylphosphonic acid epoxidase		Scavenging
1.11.2.1	K21820	unspecific peroxygenase		Scavenging
1.11.2.2	K10789	myeloperoxidase		Scavenging	Scavenging
1.11.2.3	K17991	plant seed peroxygenase		Scavenging
1.11.2.4	K15629	fatty-acid peroxygenase		Scavenging
1.11.2.5	K20208	3-methyl-L-tyrosine peroxygenase		Scavenging
1.11.2.6	K24287	L-tyrosine peroxygenase		Scavenging
1.14.18.1	K00505	tyrosinase		Scavenging
1.16.3.2	K00522;K02217	bacterial non-heme ferritin		Scavenging
1.21.98.2	K19885	dichlorochromopyrrolate synthase		Scavenging
1.10.3.17	K12262	superoxide oxidase	Scavenging
1.10.3.17	K12262	superoxide oxidase	Production
1.7.2.1	K00368	nitrite reductase (NO-forming)			Production
1.7.2.5	K04561	nitric oxide reductase (cytochrome c)			Production
1.7.2.7	K20932;K20933;K20934	hydrazine synthase			Production
1.7.6.1	K22962	nitrite dismutase			Production
1.14.13.39	K13240;K13241;K13242;K13427	nitric-oxide synthase (NADPH)			Production
1.7.2.1	K00368	nitrite reductase (NO-forming)			Scavenging
1.7.2.5	K04561	nitric oxide reductase (cytochrome c)			Scavenging
1.14.12.17	K05916	nitric oxide dioxygenase			Scavenging

Table 4: Metadata for each organism

Genus	species	Strain	FileName	Marine	Ome	Taxa	PennateCentric	PennateCentric_citekey	Rad1_um	Rad2_um	Rad3_um	Rad_citekey	Flagella	Flagella_citekey	GenomeSize_mbp	GeneModels_count	Genome_ref	Genome_citekey	Database	AccessionInfo	LiveLink	Latitude	Longitude	LogLat_citekey	ColonySpecies	Colony_citekey	Notes
Guillardia	theta	CCMP2712	Guillardia_theta_CCMP2712-aa-gen	yes	Genome	Cryptophyte			2.500	2.500	4.750	[158]	yes	[159]	87.16000	24840		[160]	JGI	16067	https://mycocosm.jgi.doe.gov/Guith1/Guith1.home.html	41.22640	-73.063900	[158]	0	[158]
Guillardia	theta	CCMP2712	Guillardia_theta_CCMP2712-dna-trans	yes	Transcriptome	Cryptophyte			2.500	2.500	4.750	[158]	yes	[159]	1.00000	0		[160]	JGI	16067	https://mycocosm.jgi.doe.gov/Guith1/Guith1.home.html	41.22640	-73.063900	[158]	0	[158]
Phaeodactylum	tricornutum	CCAP1055/1	Phaeodactylum_tricornutum_CCAP10551-aa-gen	yes	Genome	Diatom	Pennate	[161]	1.750	1.750	21.000	[161]	no	[162]	27.45070	10402		[163]	NCBI	ASM15095v2	https://www.ncbi.nlm.nih.gov/assembly/GCF_000150955.2/	54.00000	4.000000	[158]	0	[164]
Phaeodactylum	tricornutum	CCAP1055/1	Phaeodactylum_tricornutum_CCAP10551-dna-trans	yes	Transcriptome	Diatom	Pennate	[161]	1.750	1.750	21.000	[161]	no	[162]	1.00000	0		[163]	NCBI	ASM15095v2	https://www.ncbi.nlm.nih.gov/assembly/GCF_000150955.2/	54.00000	4.000000	[158]	0	[164]
Fistulifera	solaris	JPCC_DA0580	Fistulifera_solaris_JPCCDA0580-aa-gen	yes	Genome	Diatom	Pennate	[165]	1.900	1.900	3.375	[165]	no	[166]	49.74000	20429		[167]	JGI	Fistulifera solaris JPCC DA0580: Fisso1_GeneCatalog_proteins_20200805.aa.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Fisso0	28.15000	129.240000	[165]	0	[165]
Fistulifera	solaris	JPCC_DA0580	Fistulifera_solaris_JPCCDA0580-dna-trans	yes	Transcriptome	Diatom	Pennate	[165]	1.900	1.900	3.375	[165]	no	[166]	1.00000	0		[167]	JGI	Fistulifera solaris JPCC DA0580: Fisso1_GeneCatalog_transcripts_20200805.nt.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Fisso1	28.15000	129.240000	[165]	0	[165]
Thalassiosira	pseudonana	CCMP1335	Thalassiosira_pseudonana_CCMP1335-aa-gen	yes	Genome	Diatom	Centric	[158]	2.250	2.250	2.500	[158]	no	[168]	32.10000	11776		[169]	PicoPlaza	proteome.tps.tfa.gz	https://bioinformatics.psb.ugent.be/plaza/versions/pico-plaza/download	40.75600	-72.820000	[158]	0	[170]
Thalassiosira	pseudonana	CCMP1335	Thalassiosira_pseudonana_CCMP1335-dna-trans	yes	Transcriptome	Diatom	Centric	[158]	2.250	2.250	2.500	[158]	no	[168]	1.00000	0		[169]	NCBI	ASM14940v2	https://www.ncbi.nlm.nih.gov/genome/?term=txid35128[orgn]	40.75600	-72.820000	[158]	0	[170]
Thalassiosira	oceanica	CCMP1005	Thalassiosira_oceanica_CCMP1005-aa-gen	yes	Genome	Diatom	Centric	[158]	4.000	4.000	4.000	[158]	no	[166]	92.19000	34642		[171]	NCBI	PRJNA36595	https://www.ncbi.nlm.nih.gov/genome/3436	33.18330	-65.850000	[158]	0	[172]
Thalassiosira	oceanica	CCMP1005	Thalassiosira_oceanica_CCMP1005-dna-trans	yes	Transcriptome	Diatom	Centric	[158]	4.000	4.000	4.000	[158]	no	[166]	1.00000	0		[171]	NCBI	PRJNA36595	https://www.ncbi.nlm.nih.gov/genome/3437	33.18330	-65.850000	[158]	0	[172]
Coscinodiscus	wailesii	CCMP2513	Coscinodiscus_wailesii_CCMP2513-aa-trans	yes	Transcriptome	Diatom	Centric	[158]	44.000	44.000	44.000	[158]	no	[166]	1.00000	0		[173]	MMETSP	MMETSP1066	https://figshare.com/articles/dataset/Marine_Microbial_Eukaryotic_Transcriptome_Sequencing_Project_re-assemblies/3840153	31.43220	-80.358000	[158]	0	[174]
Chaetoceros	debilis	MM31A_1	Chaetoceros_debilis_MM31A_1-aa-trans	yes	Transcriptome	Diatom	Centric	[175]	6.500	7.500	12.000	[175]	no	[166]	1.00000	19453		[176]	iMicrobe	Chaetoceros-debilis-MM31A_1.pep.fa.gz	ftp://ftp.imicrobe.us/camera/combined_assemblies/				0	[177]
Conticribra_Thalassiosira	weissflogii	CCMP1010	Thalassiosira_weissflogii_CCMP1010-aa-trans	yes	Transcriptome	Diatom	Centric	[158]	5.500	5.500	7.750	[158]	no	[166]	1.00000	21329		[176]	iMicrobe	Thalassiosira-weissflogii-CCMP1010.pep.fa.gz	ftp://ftp.imicrobe.us/camera/combined_assemblies/	37.00000	-65.000000	[158]	0	[170]
Cyclotella	cryptica	CCMP332	Cyclotella_cryptica_CCMP332-aa-gen	yes	Genome	Diatom	Centric	[178]	4.500	4.500	7.000	[178]	no	[166]	161.70000	21121		[178]	UCLA	Nuclear genome	http://genomes.mcdb.ucla.edu/Cyclotella/download.html	41.35500	-70.655000		0	[170]
Nannochloropsis	oceanica	CCMP1779	Nannochloropsis_oceanica_CCMP1779-aa-gen	yes	Genome	Eustigmatophyte			1.500	1.500	1.500	[158]	no	[179]	28.74000	10641		[180]	JGI	1143084	https://mycocosm.jgi.doe.gov/Nanoce1779_2/Nanoce1779_2.home.html	29.00000	48.000000	[158]	0	[181]
Nannochloropsis	oceanica	CCMP1779	Nannochloropsis_oceanica_CCMP1779-dna-trans	yes	Transcriptome	Eustigmatophyte			1.500	1.500	1.500	[158]	no	[179]	1.00000	0		[180]	JGI	1143084	https://mycocosm.jgi.doe.gov/Nanoce1779_2/Nanoce1779_2.home.html	29.00000	48.000000	[158]	0	[181]
Nannochloropsis	gaditana	CCMP526	Nannochloropsis_gaditana_CCMP526-aa-gen	yes	Genome	Eustigmatophyte			1.500	1.500	2.500	[158]	no	[182]	30.30000	9052		[181]	NCBI	ASM24072v1	https://www.ncbi.nlm.nih.gov/assembly/GCF_000240725.1/	32.83330	-9.000000	[158]	0	[183]
Nannochloropsis	gaditana	CCMP526	Nannochloropsis_gaditana_CCMP526-dna-trans	yes	Transcriptome	Eustigmatophyte			1.500	1.500	2.500	[158]	no	[182]	1.00000	0		[181]	NCBI	ASM24072v1	https://www.ncbi.nlm.nih.gov/assembly/GCF_000240725.1/	32.83330	-9.000000	[158]	0	[183]
(Nannochloropsis) Microchloropsis	salina	CCMP1776	Nannochloropsis_salina_CCMP1776-aa-gen	yes	Genome	Eustigmatophyte			1.250	1.250	1.500	[158]	no	[184]	27.75730	10522		[185]	NCBI	ASM456527v1	https://www.ncbi.nlm.nih.gov/genome/75342?genome_assembly_id=739695	55.75000	-4.960000	[158]	0	[186]
Ostreococcus	tauri	RCC1115	Ostreococcus_tauri_RCC1115-aa-gen	yes	Genome	Green			0.500	0.500	0.500	[187]	no	[188]	14.76000	8218		[189]	NCBI	GCA_002158475.1	https://phycocosm.jgi.doe.gov/Ostta1115_2/Ostta1115_2.home.html	42.90000	3.030000	[187]	0	[190]
Ostreococcus	tauri	RCC1115	Ostreococcus_tauri_RCC1115-dna-trans	yes	Transcriptome	Green			0.500	0.500	0.500	[187]	no	[188]	1.00000	0		[189]	JGI	Ostreococcus tauri RCC1115 v1.0: Ostta1115_2_GeneCatalog_transcripts_20170131.nt.fasta.gz	https://phycocosm.jgi.doe.gov/Ostta1115_2/Ostta1115_2.home.html	42.90000	3.030000	[187]	0	[190]
Ostreococcus	tauri	RCC4221	Ostreococcus_tauri_RCC4221-aa-gen	yes	Genome	Green			0.500	0.500	0.500	[187]	no	[188]	13.03000	7669			NCBI	GCF_000214015.3	https://www.ncbi.nlm.nih.gov/assembly/GCF_000214015.3	42.40000	3.600000	[187]	0	[190]
Ostreococcus	tauri	RCC4221	Ostreococcus_tauri_RCC4221-dna-trans	yes	Transcriptome	Green			0.500	0.500	0.500	[187]	no	[188]	1.00000	0			NCBI	GCF_000214015.2	https://www.ncbi.nlm.nih.gov/assembly/GCF_000214015.3	42.40000	3.600000	[187]	0	[190]
Bathycoccus	prasinos	RCC1105	Bathycoccus_prasinos_RCC1105-aa-gen	yes	Genome	Green			0.750	0.750	0.750	[191]	no	[191]	15.07000	7900		[191]	NCBI	ASM222023v1	https://www.ncbi.nlm.nih.gov/genome/12309?genome_assembly_id=323984	42.45000	3.530000	[187]	0	[192]
Bathycoccus	prasinos	RCC1105	Bathycoccus_prasinos_RCC1105-dna-trans	yes	Transcriptome	Green			0.750	0.750	0.750	[191]	no	[191]	1.00000	0		[191]	NCBI	ASM222023v1	https://www.ncbi.nlm.nih.gov/genome/12309?genome_assembly_id=323984	42.45000	3.530000	[187]	0	[192]
Micromonas	pusilla	CCMP1545	Micromonas_pusilla_CCMP1545-aa-gen	yes	Genome	Green			1.250	1.250	1.500	[158]	yes	[193]	21.95830	10242		[194]	NCBI	GCA_000151265.1	https://www.ncbi.nlm.nih.gov/genome/501?genome_assembly_id=281477	50.36500	-4.170000	[158]	0	[195]
Micromonas	pusilla	CCMP1545	Micromonas_pusilla_CCMP1545-dna-trans	yes	Transcriptome	Green			1.250	1.250	1.500	[158]	yes	[193]	1.00000	0		[194]	NCBI	GCA_000151265.1	https://www.ncbi.nlm.nih.gov/genome/501?genome_assembly_id=281477	50.36500	-4.170000	[158]	0	[195]
Coccomyxa	subellipsoidea	C-169	Coccomyxa_sp_C169-aa-gen	yes	Genome	Green			2.400	2.400	3.600	[196]	no	[196]	49.00000	9629		[196]	JGI	Coccomyxa_C169_v2_filtered_proteins.fasta.gz	https://mycocosm.jgi.doe.gov/Coc_C169_1/Coc_C169_1.home.html				0	[197]
Coccomyxa	subellipsoidea	C-169	Coccomyxa_sp_C169-dna-trans	yes	Transcriptome	Green			2.400	2.400	3.600	[196]	no	[196]	1.00000	0		[196]	JGI	Coccomyxa_C169_v2_filtered_transcripts.fasta.gz	https://mycocosm.jgi.doe.gov/Coc_C169_1/Coc_C169_1.home.html				0	[197]
Dunaliella	salina	CCAP 19/18	Dunaliella_salina_CCAP1918-aa-gen	yes	Genome	Green			4.500	4.500	8.000	[198]	yes	[199]	343.70000	18801		[200]	JGI	Dunaliella salina CCAP19/18: Project: 1014865, Dunsal1_1_GeneCatalog_proteins_20200511.aa.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Dunsal1_1				0	[187]
Dunaliella	salina	CCAP 19/18	Dunaliella_salina_CCAP1918-dna-trans	yes	Transcriptome	Green			4.500	4.500	8.000	[198]	yes	[199]	1.00000	0		[200]	JGI	Dunaliella salina CCAP19/18: Project: 1014865, Dunsal1_1_GeneCatalog_transcripts_20200511.nt.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Dunsal1_1				0	[187]
Picocystis	salinarum	CCMP1897	Picocystis_salinarum_CCMP1897-aa-trans	yes	Transcriptome	Green			1.750	1.750	1.750	[158]	no	[201]	1.00000	6947		[176]	iMicrobe	Picocystis-salinarum-CCMP1897.pep.fa.gz	ftp://ftp.imicrobe.us/camera/combined_assemblies/	37.78000	-122.350000	[158]	0	[202]
Emiliania	huxleyi	CCMP1516	Emiliania_huxleyi_CCMP1516-aa-gen	yes	Genome	Haptophyte			3.250	3.250	3.250	[203]	yes	[203]	167.67600	38554		[204]	NCBI	GCA_000372725.1	https://www.ncbi.nlm.nih.gov/assembly/678008	-2.66670	-82.716700	[158]	0	[205]
Emiliania	huxleyi	CCMP1516	Emiliania_huxleyi_CCMP1516-dna-trans	yes	Transcriptome	Haptophyte			3.250	3.250	3.250	[203]	yes	[203]	1.00000	0		[204]	NCBI	GCA_000372725.1	https://www.ncbi.nlm.nih.gov/assembly/678008	-2.66670	-82.716700	[158]	0	[205]
Tisochrysis	lutea		Tisochrysis_lutea-aa-gen	yes	Transcriptome	Haptophyte			2.500	2.500	3.000	[206]	yes	[206]	54.40000	20582		[207]	SEANOE	Protein_sequencesV1	https://www.seanoe.org/data/00361/47171/				0	[206]
Aureococcus	anophagefferens	CCMP1984	Aureococcus_anophagefferens_CCMP1984-aa-gen	yes	Genome	Pelagophyte			1.750	1.750	1.750	[208]	no	[209]	56.66060	11522		[210]	NCBI	GCA_000186865.1 v 1.0	https://www.ncbi.nlm.nih.gov/assembly/GCF_000186865.1/	40.66670	-73.270000	[158]	0	[211]
Aureococcus	anophagefferens	CCMP1984	Aureococcus_anophagefferens_CCMP1984-dna-trans	yes	Transcriptome	Pelagophyte			1.750	1.750	1.750	[208]	no	[209]	1.00000	0		[210]	NCBI	GCA_000186865.1 v 1.0	https://www.ncbi.nlm.nih.gov/assembly/GCF_000186865.1/	40.66670	-73.270000	[158]	0	[211]
Pelagophyceae	sp.	CCMP2097	Pelagophyceae_sp_CCMP2097-aa-gen	yes	Genome	Pelagophyte			4.500	4.500	4.500	[158]	yes	[212]	85.82000	19402			JGI	Pelagophyceae sp. CCMP2097 v1.0: Project: 1020062, Pelago2097_1_GeneCatalog_proteins_20160408.aa.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Pelago2097_1	77.00140	-77.238300	[158]	0	[187]
Pelagophyceae	sp.	CCMP2097	Pelagophyceae_sp_CCMP2097-dna-trans	yes	Transcriptome	Pelagophyte			4.500	4.500	4.500	[158]	yes	[212]	1.00000	0			JGI	Pelagophyceae sp. CCMP2097 v1.0: Project: 1020062, Pelago2097_1_GeneCatalog_transcripts_20160408.nt.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Pelago2097_1	77.00140	-77.238300	[158]	0	[187]
Pelagococcus	subviridis	CCMP1429	Pelagococcus_subviridis_CCMP1429-aa-trans	yes	Transcriptome	Pelagophyte			1.500	1.500	1.500	[158]	yes	[213]	1.00000	21365		[176]	iMicrobe	Pelagococcus-subviridis-CCMP1429.pep.fa.gz	ftp://ftp.imicrobe.us/camera/combined_assemblies/	49.91660	-145.116600	[158]	0	[187]
Porphyridium	purpureum	CCMP1328	Porphyridium_purpureum_CCMP1328-aa-gen	yes	Genome	Red			3.250	3.250	3.250	[158]	no	[214]	19.70000	8355		[214]	RUTGERS	P. purpureumÊgenomic assembly (nucleotide)	http://cyanophora.rutgers.edu/porphyridium/	41.52640	-70.670000	[158]	0	[215]
Minidiscus	variabilis	CCMP495	Minidiscus_variabilis_CCMP495-aa-gen	yes	Genome	Diatom	Centric	[158]	1.750	1.750	6.000	[158]	no	[166]	76.19000	25179	JGI		JGI	Minidiscus variabilis CCMP495 v1.0: Project: 1094205, Mintr2_GeneCatalog_proteins_20160618.aa.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Mintr2	43.00000	-68.000000	[158]	0	[174]
Minidiscus	variabilis	CCMP495	Minidiscus_variabilis_CCMP495-dna-trans	yes	Transcriptome	Diatom	Centric	[158]	1.750	1.750	6.000	[158]	no	[166]	1.00000	0	JGI		JGI	Minidiscus variabilis CCMP495 v1.0: Project: 1094205, Mintr2_GeneCatalog_transcripts_20160618.nt.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Mintr2	43.00000	-68.000000	[158]	0	[174]
Prochlorococcus	marinus	AS9601	Prochlorococcus_marinus_AS9601-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.67000	1899		[217]	NCBI	GCF_000015645.1	https://www.ncbi.nlm.nih.gov/nuccore/NC_008816.1	19.12000	67.100000	[74]	0	[218]
Prochlorococcus	marinus marinus	CCMP1375	Prochlorococcus_marinus_marinus_CCMP1375-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.75000	1897		[219]	NCBI	GCF_000007925.1	https://www.ncbi.nlm.nih.gov/assembly/GCF_000007925.1	30.00000	-60.000000	[158]	0	[218]
Prochlorococcus	marinus	MIT9313	Prochlorococcus_marinus_MIT9313-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	2.41000	2457		[220]	NCBI	GCF_000011485.1	https://www.ncbi.nlm.nih.gov/assembly/GCF_000011485.1	37.30000	-68.140000	[74]	0	[218]
Prochlorococcus	marinus	NATL2A	Prochlorococcus_marinus_NATL2A-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.84000	2010		[217]	NCBI	GCF_000012465.1	https://www.ncbi.nlm.nih.gov/nuccore/NC_007335.2	38.59000	40.330000	[74]	0	[218]
Prochlorococcus	marinus pastoris	CCMP1986	Prochlorococcus_marinus_pastoris_CCMP1986-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.700	[158]	no	[216]	1.66000	1908		[220]	NCBI	GCF_000011465.1	https://www.ncbi.nlm.nih.gov/nuccore/NC_005072.1	35.00000	20.000000	[158]	0	[218]
Alexandrium	fundyense	CCMP1719	Alexandrium_fundyense_CCMP1719-aa-trans	yes	Transcriptome	Dinoflagellate			17.500	17.500	17.500	[158]	yes	[213]	1.00000	11897		[176]	iMicrobe	Alexandrium-fundyense-CCMP1719.pep.fa	https://datacommons.cyverse.org/browse/iplant/home/shared/imicrobe/camera/camera_mmetsp_ncgr/combined_assemblies/Alexandrium-fundyense-CCMP1719	43.10000	-70.782000	[158]	0	[221]
Amphidinium	carterae	CCMP1314	Amphidinium_carterae_CCMP1314-aa-trans	yes	Transcriptome	Dinoflagellate			5.500	5.500	8.000	[158]	yes	[213]	1.00000	42459		[176]	iMicrobe	Amphidinium-carterae-CCMP1314/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Amphidinium-carterae-CCMP1314/	41.56000	-70.583000	[158]	0	[222]
Aureoumbra	lagunensis	CCMP1510	Aureoumbra_lagunensis_CCMP1510-aa-trans	yes	Transcriptome	Pelagophyte			2.750	2.750	2.750	[158]	yes	[213]	1.00000	16737		[176]	iMicrobe	Aureoumbra-lagunensis-CCMP1510/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Aureoumbra-lagunensis-CCMP1510/	27.47080	-97.320000	[158]	0	[223]
Chaetoceros	affinis	CCMP159	Chaetoceros_affinis_CCMP159-aa-trans	yes	Transcriptome	Diatom	Centric	[158]	3.750	3.750	11.000	[158]	no	[166]	1.00000	19072		[176]	iMicrobe	Chaetoceros-affinis-CCMP159/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Chaetoceros-affinis-CCMP159/	29.42000	-86.105000	[158]	0	[187]
Chattonella	subsalsa	CCMP2191	Chattonella_subsalsa_CCMP2191-aa-trans	yes	Transcriptome	Raphidophyte			10.750	10.750	21.000	[158]	yes		1.00000	25803		[176]	iMicrobe	Chattonella-subsalsa-CCMP2191/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Chattonella-subsalsa-CCMP2191/	38.59000	-75.100000	[158]	0	[187]
Heterosigma	akashiwo	CCMP2393	Heterosigma_akashiwo_CCMP2393-aa-trans	yes	Transcriptome	Raphidophyte			6.500	6.500	9.000	[158]	yes	[224]	1.00000	40801		[176]	iMicrobe	Heterosigma-akashiwo-CCMP2393/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Heterosigma-akashiwo-CCMP2393/	38.69910	-75.109700	[158]	0	[225]
Heterosigma	akashiwo	CCMP452	Heterosigma_akashiwo_CCMP452-aa-trans	yes	Transcriptome	Raphidophyte			6.000	6.000	6.250	[158]	yes	[224]	1.00000	27465		[176]	iMicrobe	Heterosigma-akashiwo-CCMP452/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Heterosigma-akashiwo-CCMP452/	41.00000	-73.000000	[158]	0	[225]
Isochrysis	galbana	CCMP1323	Isochrysis_galbana_CCMP1323-aa-trans	yes	Transcriptome	Haptophyte			1.500	1.500	2.500	[158]	yes	[226]	1.00000	45931		[176]	iMicrobe	Isochrysis-galbana-CCMP1323/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Isochrysis-galbana-CCMP1323/	54.08500	-4.770000	[158]	0	[158]
Isochrysis	sp.	CCMP1244	Isochrysis_sp_CCMP1244-aa-trans	yes	Transcriptome	Haptophyte			2.000	2.000	2.000	[158]	yes		1.00000	38449		[176]	iMicrobe	Isochrysis-sp-CCMP1244/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Isochrysis-sp-CCMP1244/	38.30480	-69.619200	[158]	0	[158]
Lingulodinium	polyedra	CCMP1738	Lingulodinium_polyedra_CCMP1738-aa-trans	yes	Transcriptome	Dinoflagellate			17.500	17.500	18.750	[158]	yes	[213]	1.00000	104588		[176]	iMicrobe	Lingulodinium-polyedra-CCMP1738/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Lingulodinium-polyedra-CCMP1738/	27.80000	-97.130000	[158]	0	[187]
Rhodomonas	sp.	CCMP768	Rhodomonas_sp_CCMP768-aa-trans	yes	Transcriptome	Cryptophyte			4.750	4.750	8.750	[158]	yes		1.00000	31952		[176]	iMicrobe	Rhodomonas-sp-CCMP768/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Rhodomonas-sp-CCMP768/	-39.00000	176.000000	[158]	0	[187]
Scrippsiella	trochoidea	CCMP3099	Scrippsiella_trochoidea_CCMP3099-aa-trans	yes	Transcriptome	Dinoflagellate			12.500	12.500	16.000	[158]	yes	[213]	1.00000	113860		[176]	iMicrobe	Scrippsiella-trochoidea-CCMP3099/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Scrippsiella-trochoidea-CCMP3099/	27.31220	-82.601000	[158]	0	[227]
Cyanobium	sp.	NIES-981	Cyanobium_sp_NIES-981-aa-gen	yes	Genome	Prokaryote			0.380	0.380	0.650	[228]	no	[228]	3.02000	2883		[229]	NCBI	GCA_900088535.1 ASM90008853v1 scaffolds: 1 contigs: 1 N50: 3,021,545 L50: 1	https://www.ncbi.nlm.nih.gov/genome/13678?genome_assembly_id=319205				0	[230]
Lotharella	globosa	CCCM811	Lotharella_globosa_CCCM811-aa-trans	yes	Transcriptome	Green			4.600	4.600	4.600	[231]	yes	[231]	1.00000	29293		[176]	iMicrobe	Lotharella-globosa-CCCM811.pep.fa	ftp://ftp.imicrobe.us/camera/combined_assemblies/	13.83330	144.750000	[158]	0	[232]	CCCM811 is also known as CCMP2314 or CCMP1729
Prochlorococcus	sp.	MIT0601	Prochlorococcus_sp._MIT0601-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.71000	1854		[233]	NCBI	GCA_000760175.1	https://www.ncbi.nlm.nih.gov/genome/13712?genome_assembly_id=210094	22.75000	-158.000000	[233]	0	[218]
Prochlorococcus	marinus	GP2	Prochlorococcus_marinus_GP2-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.62000	1845		[233]	NCBI	GCA_000759885.1 ASM75988v1 scaffolds: 11 contigs: 11 N50: 416,038 L50: 2	https://www.ncbi.nlm.nih.gov/genome/164?genome_assembly_id=209980	8.00000	136.000000	[234]	0	[218]
Prochlorococcus	sp.	MIT0604	Prochlorococcus_sp._MIT0604-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.78000	2040		[233]	NCBI	GCA_000757845.1 ASM75784v1 scaffolds: 1 contigs: 1 N50: 1,780,061 L50: 1	https://www.ncbi.nlm.nih.gov/genome/13712?genome_assembly_id=209903	22.75000	-158.000000	[235]	0	[218]
Prochlorococcus	sp.	MIT0801	Prochlorococcus_sp._MIT0801-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.93000	2171		[233]	NCBI	GCA_000757865.1 ASM75786v1 scaffolds: 1 contigs: 1 N50: 1,929,203 L50: 1	https://www.ncbi.nlm.nih.gov/genome/13712?genome_assembly_id=209904	31.67000	-64.170000	[233]	0	[218]
Prochlorococcus	sp.	MIT0602	Prochlorococcus_sp._MIT0602-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.75092	1897		[233]	NCBI	GCA_000760195.1 ASM76019v1 scaffolds: 9 contigs: 9 N50: 511,704 L50: 2	https://www.ncbi.nlm.nih.gov/genome/13712?genome_assembly_id=210095	22.75000	-158.000000	[233]	0	[218]
Prochlorococcus	sp.	MIT0603	Prochlorococcus_sp._MIT0603-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.75248	1896		[233]	NCBI	GCA_000760215.1 ASM76021v1 scaffolds: 7 contigs: 7 N50: 434,668 L50: 2	https://www.ncbi.nlm.nih.gov/genome/13712?genome_assembly_id=210096	22.75000	-158.000000	[233]	0	[218]
Prochlorococcus	sp.	SS52	Prochlorococcus_sp._SS52-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.75405	1919		[233]	NCBI	GCA_000760375.1 ASM76037v1 scaffolds: 22 contigs: 22 N50: 124,224 L50: 5	https://www.ncbi.nlm.nih.gov/genome/13712?genome_assembly_id=210100	28.98000	-64.350000	[236]	0	[218]
Prochlorococcus	sp.	MIT0701	Prochlorococcus_sp._MIT0701-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	2.59257	2591		[233]	NCBI	GCA_000760295.1 ASM76029v1 scaffolds: 53 contigs: 53 N50: 84,463 L50: 9	https://www.ncbi.nlm.nih.gov/genome/13712?genome_assembly_id=210097	-13.45000	-0.040000	[233]	0	[218]
Prochlorococcus	sp.	MIT0702	Prochlorococcus_sp._MIT0702-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	2.58306	5288		[233]	NCBI	GCA_000760315.1 ASM76031v1 scaffolds: 61 contigs: 61 N50: 76,101 L50: 10	https://www.ncbi.nlm.nih.gov/genome/13712?genome_assembly_id=210098	-13.45000	-0.040000	[233]	0	[218]
Prochlorococcus	sp.	MIT0703	Prochlorococcus_sp._MIT0703-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	2.57506	2591		[233]	NCBI	GCA_000760335.1 ASM76033v1 scaffolds: 61 contigs: 61 N50: 81,186 L50: 10	https://www.ncbi.nlm.nih.gov/genome/13712?genome_assembly_id=210099	-13.45000	-0.040000	[233]	0	[218]
Prochlorococcus	marinus	SB	Prochlorococcus_marinus_SB-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.66982	1874		[233]	NCBI	GCA_000760115.1 ASM76011v1 scaffolds: 4 contigs: 4 N50: 1,237,529 L50: 1	https://www.ncbi.nlm.nih.gov/genome/164?genome_assembly_id=209989	35.00000	138.300000	[234]	0	[218]
Prochlorococcus	marinus	SS35	Prochlorococcus_marinus_SS35-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.75101	1895		[233]	NCBI	GCA_000760275.1 ASM76027v1 scaffolds: 9 contigs: 9 N50: 446,270 L50: 2	https://www.ncbi.nlm.nih.gov/genome/164?genome_assembly_id=209993	28.98000	-64.350000	[236]	0	[218]
Prochlorococcus	marinus	SS51	Prochlorococcus_marinus_SS51-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.74698	1908		[233]	NCBI	GCA_000760355.1 ASM76035v1 scaffolds: 12 contigs: 12 N50: 232,789 L50: 3	https://www.ncbi.nlm.nih.gov/genome/164?genome_assembly_id=209994	28.98000	-64.350000	[236]	0	[218]
Prochlorococcus	marinus	SS2	Prochlorococcus_marinus_SS2-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.75277	1903		[233]	NCBI	GCA_000760255.1 ASM76025v1 scaffolds: 19 contigs: 19 N50: 187,268 L50: 3	https://www.ncbi.nlm.nih.gov/genome/164?genome_assembly_id=209992	28.98000	-64.350000	[236]	0	[218]
Prochlorococcus	marinus	MIT9314	Prochlorococcus_marinus_MIT9314-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.69056	1937		[233]	NCBI	GCA_000760035.1 ASM76003v1 scaffolds: 16 contigs: 16 N50: 221,824 L50: 3	https://www.ncbi.nlm.nih.gov/genome/164?genome_assembly_id=209985	37.51000	-64.240000	[236]	0	[218]
Prochlorococcus	marinus	MIT9321	Prochlorococcus_marinus_MIT9321-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.65866	1903		[233]	NCBI	GCA_000760055.1 ASM76005v1 scaffolds: 10 contigs: 10 N50: 259,210 L50: 3	https://www.ncbi.nlm.nih.gov/genome/164?genome_assembly_id=209986	1.00000	-92.000000	[236]	0	[218]
Prochlorococcus	marinus	MIT9322	Prochlorococcus_marinus_MIT9322-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.65755	1901		[233]	NCBI	GCA_000760075.1 ASM76007v1 scaffolds: 11 contigs: 11 N50: 367,597 L50: 2	https://www.ncbi.nlm.nih.gov/genome/164?genome_assembly_id=209987	0.27000	-93.000000	[236]	0	[218]
Prochlorococcus	marinus	MIT9401	Prochlorococcus_marinus_MIT9401-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.66681	1919		[233]	NCBI	GCA_000760095.1 ASM76009v1 scaffolds: 17 contigs: 17 N50: 110,519 L50: 4	https://www.ncbi.nlm.nih.gov/genome/164?genome_assembly_id=209988	35.50000	-70.400000	[236]	0	[218]
Prochlorococcus	marinus	EQPAC1	Prochlorococcus_marinus_EQPAC1-aa-gen	yes	Genome	Prokaryote			0.350	0.350	0.550	[74]	no	[216]	1.65474	1907		[233]	NCBI	GCA_000759875.1 ASM75987v1 scaffolds: 8 contigs: 8 N50: 328,627 L50: 2	https://www.ncbi.nlm.nih.gov/genome/164?genome_assembly_id=209979	0.00000	-180.000000	[236]	0	[218]
Synechococcus	sp.	WH7803	Synechococcus_sp._WH7803-aa-gen	yes	Genome	Prokaryote			0.500	0.500	0.500	[187]	no	[237]	2.36698	2586			NCBI	GCA_000063505.1 ASM6350v1 scaffolds: 1 contigs: 1 N50: 2,366,980 L50: 1	https://www.ncbi.nlm.nih.gov/genome/13522?genome_assembly_id=174736	33.75000	-67.500000	[187]	0	[238]
Synechococcus	sp.	WH8101	Synechococcus_sp._WH8101-aa-gen	yes	Genome	Prokaryote			0.500	0.500	0.500	[239]	no	[237]	2.63029	2816			NCBI	GCA_004209775.1 ASM420977v1 scaffolds: 1 contigs: 1 N50: 2,630,292 L50: 1	https://www.ncbi.nlm.nih.gov/genome/13522?genome_assembly_id=451744	41.31410	-70.401300	[240]	0	[238]
Synechococcus	sp.	WH8103	Synechococcus_sp._WH8103-aa-gen	yes	Genome	Prokaryote			0.500	0.500	0.500	[239]	no	[237]	2.42969	2648			NCBI	GCA_001182765.1 WH8103.1 scaffolds: 1 contigs: 1 N50: 2,429,688 L50: 1	https://www.ncbi.nlm.nih.gov/genome/13522?genome_assembly_id=240763	28.50000	-67.390000	[187]	0	[238]
Synechococcus	sp.	WH8109	Synechococcus_sp._WH8109-aa-gen	yes	Genome	Prokaryote			0.500	0.500	0.500	[239]	no	[237]	2.11151	2363			NCBI	GCA_000161795.2 ASM16179v2 scaffolds: 1 contigs: 1 N50: 2,111,515 L50: 1	https://www.ncbi.nlm.nih.gov/genome/13522?genome_assembly_id=228479	39.48000	-70.460000	[187]	0	[238]
Synechococcus	sp.	PCC7002	Synechococcus_sp._PCC7002-aa-gen	yes	Genome	Prokaryote			0.500	0.500	0.500	[239]	no	[237]	3.40993	2872			NCBI	GCA_000019485.1 ASM1948v1 scaffolds: 7 contigs: 7 N50: 3,008,047 L50: 1	https://www.ncbi.nlm.nih.gov/genome/13522?genome_assembly_id=300956				0	[238]
Synechococcus	sp.	MEDNS5	Synechococcus_sp._MEDNS5-aa-gen	yes	Genome	Prokaryote			0.500	0.500	0.500	[187]	no	[237]	2.43587	2607			NCBI	GCA_014279875.1 ASM1427987v1 scaffolds: 1 contigs: 1 N50: 2,435,869 L50: 1	https://www.ncbi.nlm.nih.gov/genome/13522?genome_assembly_id=978542	41.00000	6.000000	[187]	0	[238]
Synechococcus	sp.	MITS9220	Synechococcus_sp._MITS9220-aa-gen	yes	Genome	Prokaryote			0.500	0.500	0.500	[187]	no	[237]	2.42417	2650			NCBI	GCA_014304815.1 ASM1430481v1 scaffolds: 1 contigs: 1 N50: 2,424,175 L50: 1	https://www.ncbi.nlm.nih.gov/genome/13522?genome_assembly_id=979223				0	[238]
Synechococcus	sp.	NIES-970	Synechococcus_sp._NIES970-aa-gen	yes	Genome	Prokaryote			0.750	0.750	0.750		no	[237]	3.12386	2685		[241]	NCBI	GCA_002356215.1 ASM235621v1 scaffolds: 5 contigs: 5 N50: 2,836,539 L50: 1	https://www.ncbi.nlm.nih.gov/genome/13522?genome_assembly_id=331806	27.00000	129.000000	[241]	0	[238]
Cyanobium	sp.	LEGE06143	Cyanobium_sp_LEGE06143-aa-gen	yes	Genome	Prokaryote			0.600	0.600	0.600	[242]	no	[243]	2.57073	2780			NCBI	GCA_015207535.1 ASM1520753v1 scaffolds: 317 contigs: 317 N50: 11,389 L50: 69	https://www.ncbi.nlm.nih.gov/genome/13678?genome_assembly_id=1482232	37.07156	-8.774722	[242]	0	[230]
Cyanobium	sp.	LEGE06113	Cyanobium_sp_LEGE06113-aa-gen	yes	Genome	Prokaryote			0.600	0.600	0.600	[242]	no	[243]	2.93701	3076			NCBI	GCA_015207615.1 ASM1520761v1 scaffolds: 18 contigs: 18 N50: 328,991 L50: 3	https://www.ncbi.nlm.nih.gov/genome/13678?genome_assembly_id=1482231	41.04954	-8.655339	[242]	0	[230]
Synechococcus	sp.	SynAce01	Synechococcus_sp._SynAce01-aa-gen	yes	Genome	Prokaryote			0.500	0.500	0.500	[239]	no	[237]	2.75000	2950			JGI	Synechococcus sp. SynAce01: 118502.assembled.fna	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=IMG_2718218441	-68.27000	78.120000		0	[238]
Gephyrocapsa	oceanica	RCC1303	Gephyrocapsa_oceanica_RCC1303-aa-trans	yes	Transcriptome	Haptophyte			2.300	2.300	2.300	[187]	no	[243]	1.00000	38577		[176]	iMicrobe	Gephyrocapsa-oceanica-RCC1303.pep	ftp://ftp.imicrobe.us/camera/combined_assemblies/	45.00000	-1.080000	[187]	0	[244]
Fragilariopsis	cylindrus	CCMP1102	Fragilariopsis_cylindrus_CCMP1102-aa-gen	yes	Genome	Diatom	Pennate	[245]	1.500	1.500	2.500	[158]	no	[166]	80.50000	27137		[245]	JGI	Fragilariopsis cylindrus CCMP 1102: Project: 16035, Fracy1_GeneModels_FilteredModels1_aa.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Fracy1	-64.08000	-48.703300	[158]	1	[246]
Fragilariopsis	cylindrus	CCMP1102	Fragilariopsis_cylindrus_CCMP1102-dna-trans	yes	Transcriptome	Diatom	Pennate	[245]	1.500	1.500	2.500	[158]	no	[166]	1.00000	0		[245]	JGI	Fragilariopsis cylindrus CCMP 1102: Project: 16035, Fracy1_GeneModels_FilteredModels1_nt.fasta.gz	https://mycocosm.jgi.doe.gov/Fracy1/Fracy1.home.html	-64.08000	-48.703300	[158]	1	[246]
Pseudo-nitzschia	multistriata	B856	Pseudo-nitzschia_multistriata_B856-aa-gen	yes	Genome	Diatom	Pennate	[247]	1.650	1.650	23.500	[247]	no	[247]	56.76520	12039		[248]	NCBI	ASM90066040v1	https://www.ncbi.nlm.nih.gov/assembly/GCA_900660405.1/				1	[249]
Pseudo-nitzschia	multiseries	CLN-47	Pseudo-nitzschia_multiseries_CLN-47-aa-gen	yes	Genome	Diatom	Pennate	[249]	2.250	2.250	33.300	[249]	no	[250]	218.73000	19703			JGI	1076539	https://genome.jgi.doe.gov/portal/PsenitmultiCLN47_FD/PsenitmultiCLN47_FD.info.html				1	[251]
Pseudo-nitzschia	multiseries	CLN-47	Pseudo-nitzschia_multiseries_CLN-47-dna-trans	yes	Transcriptome	Diatom	Pennate	[249]	2.250	2.250	33.300	[249]	no	[250]	1.00000	0			JGI	1076539	https://genome.jgi.doe.gov/portal/PsenitmultiCLN47_FD/PsenitmultiCLN47_FD.info.html				1	[251]
Nitzschia	palea		Nitzschia_palea-dna-trans	yes	Transcriptome	Diatom	Pennate	[252]	1.750	1.750	13.500	[252]	no	[166]	1.00000	15885		[253]	ENA	GHBX01000000	https://www.ebi.ac.uk/ena/data/view/GHBX01000000				1	[254]
Leptocylindrus	danicus		Leptocylindrus_danicus-dna-trans	yes	Transcriptome	Diatom	Centric	[175]	5.250	5.250	35.000	[175]	no	[166]	1.00000	15701		[255]	ENA	GAUB01000000	https://www.ebi.ac.uk/ena/data/view/GAUB01000000				1	[256]
Thalassiosira	antarctica	CCMP982	Thalassiosira_antarctica_CCMP982-aa-trans	yes	Transcriptome	Diatom	Centric	[158]	5.500	5.500	10.000	[158]	no	[166]	1.00000	31618		[176]	iMicrobe	Thalassiosira-antarctica-CCMP982.pep.fa.gz	ftp://ftp.imicrobe.us/camera/combined_assemblies/	59.50000	10.600000	[158]	1	[174]
Thalassiosira	rotula	CCMP3096	Thalassiosira_rotula_CCMP3096-aa-trans	yes	Transcriptome	Diatom	Centric	[158]	8.750	8.750	18.500	[158]	no	[166]	1.00000	26935		[176]	iMicrobe	Thalassiosira-rotula-CCMP3096.pep.fa.gz	ftp://ftp.imicrobe.us/camera/combined_assemblies/	49.65000	-127.433800	[158]	1	[257]
Chaetoceros	neogracile	CCMP1317	Chaetoceros_neogracile_CCMP1317-aa-trans	yes	Transcriptome	Diatom	Centric	[158]	1.750	1.750	4.750	[158]	no	[166]	1.00000	27860		[176]	iMicrobe	Chaetoceros-neogracile-CCMP1317.pep.fa.gz	ftp://ftp.imicrobe.us/camera/combined_assemblies/	32.85000	-117.350000	[158]	1	[258]
Thalassiosira	minuscula	CCMP1093	Thalassiosira_miniscula_CCMP1093-aa-trans	yes	Transcriptome	Diatom	Centric	[158]	6.000	6.000	7.500	[158]	no	[166]	1.00000	44803		[176]	iMicrobe	Thalassiosira-minuscula-CCMP1093.pep.fa.gz	ftp://ftp.imicrobe.us/camera/combined_assemblies/	32.90000	-117.255000	[158]	1	[259]
Ditylum	brightwellii	GSO103	Ditylum_brightwellii_GSO103-aa-trans	yes	Transcriptome	Diatom	Centric	[175]	33.500	33.500	85.000	[175]	no	[166]	1.00000	24623		[176]	iMicrobe	Ditylu-brightwellii-GSO103.pep.fa.gz	ftp://ftp.imicrobe.us/camera/combined_assemblies/				1	[260]
Chaetoceros	curvisetus		Chaetoceros_curvisetus-aa-trans	yes	Transcriptome	Diatom	Centric	[161]	5.750	8.750	11.250	[161]	no	[166]	1.00000	23542		[176]	iMicrobe	Chaetoceros-curvisetus .pep.fa.gz	ftp://ftp.imicrobe.us/camera/combined_assemblies/				1	[261]
(Symbiodinium) Breviolum	minutum		Symbiodinium_minutum-aa-gen	yes	Genome	Symbiodinium			3.750	3.750	3.750	[262]	yes	[263]	1500.00000	41925		[264]	MGU	symbB.v1.2.augustus.prot.fa.gz	https://marinegenomics.oist.jp/symb/viewer/download?project_id=21				1	[265]
(Symbiodinium) Breviolum	minutum		Symbiodinium_minutum-dna-trans	yes	Transcriptome	Symbiodinium			3.750	3.750	3.750	[262]	yes	[263]	1.00000	0		[264]	MGU	symbB1_v1.0.transcriptome_assembly.fa.gz	https://marinegenomics.oist.jp/symb/viewer/download?project_id=21				1	[265]
(Symbiodinium) Cladocopium	goreaui		Symbiodinium_goreaui-aa-gen	yes	Genome	Symbiodinium			3.350	3.350	4.150	[266]	yes	[213]	705.00000	65832		[264]	MGU	symC_aug_40.aa.gz	https://marinegenomics.oist.jp/symb/viewer/download?project_id=40				1	[267]	MesophyticColony
(Symbiodinium) Cladocopium	goreaui		Symbiodinium_goreaui-dna-trans	yes	Transcriptome	Symbiodinium			3.350	3.350	3.350	[266]	yes	[213]	1.00000	0		[264]	MGU	symC_transcriptome_40.fasta.gz	https://marinegenomics.oist.jp/symb/viewer/download?project_id=40				1	[267]	MesophyticColony
Polarella	glacialis	CCMP1383	Polarella_glacialis_CCMP1383-aa-gen	yes	Genome	Dinoflagellate			3.000	3.000	6.250	[158]	yes	[268]	2980.00000	58232		[269]	AARNET	Polarella_glacialis_CCMP1383_PredGene_v1.pep.fa	https://cloudstor.aarnet.edu.au/plus/s/Nx08JEMt7FjK3zY	-77.83330	163.000000	[158]	1	[270]
Polarella	glacialis	CCMP2088	Polarella_glacialis_CCMP2088-aa-gen	yes	Genome	Dinoflagellate			4.500	4.500	8.000	[158]	yes	[268]	2760.00000	51713		[269]	AARNET	Polarella_glacialis_CCMP2088_PredGene_v1.pep.fa	https://cloudstor.aarnet.edu.au/plus/s/Nx08JEMt7FjK3zY	78.59780	-74.499200	[158]	1	[270]
Phaeocystis	antarctica	CCMP1374	Phaeocystis_antarctica_CCMP1374-aa-gen	yes	Genome	Haptophyte			3.250	3.250	3.250	[271]	yes	[272]	198.94000	41088	JGI		JGI	Phaeocystis antarctica CCMP1374 v2.2: Project: 1070272, Phaant1_GeneCatalog_proteins_20181014.aa.fasta.gz	https://phycocosm.jgi.doe.gov/Phaant1/Phaant1.info.html	-77.83330	163.000000	[158]	1	[273]
Phaeocystis	antarctica	CCMP1374	Phaeocystis_antarctica_CCMP1374-dna-trans	yes	Transcriptome	Haptophyte			3.250	3.250	3.250	[271]	yes	[272]	1.00000	0	JGI		JGI	Phaeocystis antarctica CCMP1374 v2.2: Project: 1070272, Phaant1_GeneCatalog_transcripts_20181014.nt.fasta.gz	https://phycocosm.jgi.doe.gov/Phaant1/Phaant1.info.html	-77.83330	163.000000	[158]	1	[273]
Phaeocystis	globosa	Pg-G	Phaeocystis_globosa_Pg-G-aa-gen	yes	Genome	Haptophyte			3.450	3.450	3.450	[274]	yes	[274]	155.85000	32196	JGI		JGI	Phaeocystis globosa Pg-G v2.3: Project: 1070438, Phaglo1_GeneModels_PhytozomeGeneModels_proteins_20190222.aa.fasta.gz	https://mycocosm.jgi.doe.gov/Phaglo1/Phaglo1.home.html				1	[158]
Phaeocystis	globosa	Pg-G	Phaeocystis_globosa_Pg-G-dna-trans	yes	Transcriptome	Haptophyte			3.450	3.450	3.450	[274]	yes	[274]	1.00000	0	JGI		JGI	Phaeocystis globosa Pg-G v2.3: Project: 1070438, Phaglo1_GeneCatalog_transcripts_20181013.nt.fasta.gz	https://mycocosm.jgi.doe.gov/Phaglo1/Phaglo1.home.html				1	[158]
Alexandrium	temarense	CCMP1771	Alexandrium_temarense_CCMP1771-aa-trans	yes	Transcriptome	Dinoflagellate			18.750	18.750	19.500	[158]	yes	[213]	1.00000	135584		[176]	iMicrobe	Alexandrium-temarense-CCMP1771/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Alexandrium-temarense-CCMP1771/	50.36000	-4.150000	[158]	1	[275]
Amphora	coffeaeformis	CCMP127	Amphora_coffeaeformis_CCMP127-aa-trans	yes	Transcriptome	Diatom	Pennate	[158]	3.000	3.000	9.250	[158]	no	[166]	1.00000	15523		[176]	iMicrobe	Amphora-coffeaeformis-CCMP127/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Amphora-coffeaeformis-CCMP127/	41.52500	-70.673600	[158]	1	[276]
Asterionellopsis	glacialis	CCMP134	Asterionellopsis_glacialis_CCMP134-aa-trans	yes	Transcriptome	Diatom	Pennate	[158]	4.500	4.500	9.500	[158]	no	[166]	1.00000	23387		[176]	iMicrobe	Asterionellopsis-glacialis-CCMP134/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Asterionellopsis-glacialis-CCMP134/	32.65550	-117.140000	[158]	1	[277]
Extubocellulus	spinifer	CCMP396	Extubocellulus_spinifer_CCMP396-aa-trans	yes	Transcriptome	Diatom	Centric	[158]	1.250	1.250	2.750	[158]	no	[166]	1.00000	53419		[176]	iMicrobe	Extubocellulus-spinifer-CCMP396/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Extubocellulus-spinifer-CCMP396/	31.31720	-113.560000	[158]	1	[278]
Skeletonema	menzelii	CCMP793	Skeletonema_menzelii_CCMP793-aa-trans	yes	Transcriptome	Diatom	Centric	[158]	2.750	2.750	3.000	[158]	no	[166]	1.00000	16088		[176]	iMicrobe	Skeletonema-menzelii-CCMP793/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Skeletonema-menzelii-CCMP793/	41.56600	-70.584200	[158]	1	[158]
Cyanobium	sp.	PCC7001	Cyanobium_sp_PCC7001-aa-gen	yes	Genome	Prokaryote			0.380	0.380	0.650	[279]	no	[279]	2.83000	2725	NCBI		NCBI	GCA_000155635.1	https://www.ncbi.nlm.nih.gov/genome/13678?genome_assembly_id=175233				1	[230]
Prasinoderma	coloniale	CCMP1413	Prasinoderma_coloniale_CCMP1413-aa-gen	yes	Genome	Green			1.250	1.250	1.250	[158]	no		25.32000	7139	JGI		JGI	Prasinoderma coloniale CCMP1413: Praco1_ExternalModels_proteins_20200803.aa.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Praco1	35.00000	-70.000000	[158]	1	[280]
Nitzschia	frigida		Nitzschia_frigida-dna-trans	yes	Transcriptome	Diatom	Pennate	[281]	2.250	20.000	20.000	[282]	no	[166]	1.00000	0		[283]	Rokitta 2019	N.frigida contigs.fasta	https://zenodo.org/record/3361258#.YD1Uj5NKjDI				1	[284]
Thalassiosira	hyalina		Thalassiosira_hyalina-dna-trans	yes	Transcriptome	Diatom	Centric	[281]	9.500	9.500	16.000	[282]	no	[166]	1.00000	0		[283]	Rokitta 2019	T.hyalina contigs.fasta	https://zenodo.org/record/3361258#.YD1Uj5NKjDI				1	[285]
Crocosphaera	watsonii	WH8501	Crocosphaera_watsonii_WH8501-aa-gen	yes	Genome	Prokaryote			1.500	1.500	1.500	[286]	no	[243]	6.24000	6302	NCBI	[287]	NCBI	GCF_000167195.1_ASM16719v1_protein.faa	https://www.ncbi.nlm.nih.gov/genome/1130?genome_assembly_id=170600	-28.00000	-48.000000	[286]	1	[288]
Crocosphaera	watsonii	WH0401	Crocosphaera_watsonii_WH0401-aa-gen	yes	Genome	Prokaryote			1.470	1.470	1.470	[286]	no	[243]	4.55000	4718	NCBI		NCBI	GCF_001039615.1_WH0401_v1_protein.faa	https://www.ncbi.nlm.nih.gov/genome/1130?genome_assembly_id=233292	6.00000	-49.000000	[286]	1	[288]
Crocosphaera	watsonii	WH0003	Crocosphaera_watsonii_WH0003-aa-gen	yes	Genome	Prokaryote			2.540	2.540	2.540	[286]	no	[243]	5.89000	5877	NCBI	[287]	NCBI	GCA_000235665.2 ASM23566v2	https://www.ncbi.nlm.nih.gov/genome/1130?genome_assembly_id=170601	22.00000	-158.000000	[286]	1	[288]
Crocosphaera	watsonii	WH0402	Crocosphaera_watsonii_WH0402-aa-gen	yes	Genome	Prokaryote			2.280	2.280	2.280	[286]	no	[243]	5.88000	5963	NCBI		NCBI	GCA_001039635.1 WH0402_v1	https://www.ncbi.nlm.nih.gov/genome/1130?genome_assembly_id=233293	-11.00000	-32.000000	[286]	1	[288]
Crocosphaera	watsonii	WH0005	Crocosphaera_watsonii_WH0005-aa-gen	yes	Genome	Prokaryote			2.150	2.150	2.150	[286]	no	[243]	5.96000	6029	NCBI		NCBI	GCA_001050835.1 ASM105083v1	https://www.ncbi.nlm.nih.gov/genome/1130?genome_assembly_id=234839	21.00000	-157.000000	[286]	1	[288]
Crocosphaera	subtropica	ATCC51142	Crocosphaera_subtropica_ATCC51142-aa-gen	yes	Genome	Prokaryote			2.250	2.250	2.250	[289]	no	[243]	5.46038	5063		[290]	NCBI	GCA_000017845.1 ASM1784v1 scaffolds: 6 contigs: 6 N50: 4,934,271 L50: 1	https://www.ncbi.nlm.nih.gov/genome/?term=txid43989[Organism:noexp]	27.78000	-97.110000		1	[291]
Fragilariopsis	kerguelensis	L2_C3	Fragilariopsis_kerguelensis_L2_C3-aa-trans	yes	Transcriptome	Diatom	Pennate	[292]	3.900	3.900	15.365	[293]	no	[166]	1.00000	61393		[176]	iMicrobe	Fragilariopsis-kerguelensis-L2_C3.pep	ftp://ftp.imicrobe.us/camera/combined_assemblies/				1	[294]
Pseudo-nitzschia	fradulenta	WWA7	Pseudo-nitzschia_fradulenta_WWA7-aa-trans	yes	Transcriptome	Diatom	Pennate	[249]	3.000	3.000	57.250	[295]	no	[166]	1.00000	51324		[176]	iMicrobe	Pseudo_nitzschia-fradulenta-WWA7.pep	ftp://ftp.imicrobe.us/camera/combined_assemblies/				1	[296]
Pseudo-nitzschia	australis	10249_10_AB	Pseudo-nitzschia_australis_10249_10_AB-aa-trans	yes	Transcriptome	Diatom	Pennate	[249]	3.325	3.325	51.500	[295]	no	[166]	1.00000	21468		[176]	iMicrobe	Pseudo_nitzschia-australis-10249_10_AB.pep	ftp://ftp.imicrobe.us/camera/combined_assemblies/				1	[297]	Another article: https://www.tandfonline.com/doi/pdf/10.2216/11-37.1?needAccess=true
Thalassiothrix	antarctica	L6_D1	Thalassiothrix_antarctica_L6_D1-aa-trans	yes	Transcriptome	Diatom	Pennate	[298]	2.750	2.750	680.000	[299]	no	[166]	1.00000	26469		[176]	iMicrobe	Thalassiothrix-antarctica-L6_D1.pep	ftp://ftp.imicrobe.us/camera/combined_assemblies/				1	[300]
Skeletonema	marinoi	SkelA	Skeletonema_marinoi_SkelA-aa-trans	yes	Transcriptome	Diatom	Centric	[301]	3.950	3.950	5.975	[302]	no	[302]	1.00000	21103		[176]	iMicrobe	Skeletonema-marinoi-SkelA.pep	ftp://ftp.imicrobe.us/camera/combined_assemblies/				1	[303]
Skeletonema	dohrnii	SkelB	Skeletonema_dohrnii_SkelB-aa-trans	yes	Transcriptome	Diatom	Centric	[158]	2.250	2.250	16.000	[304]	no	[304]	1.00000	23719		[176]	iMicrobe	Skeletonema-dohrnii-SkelB.pep	ftp://ftp.imicrobe.us/camera/combined_assemblies/				1	[305]
Symbiodinium	microadriaticum	CCMP2467	Symbiodinium_microadriaticum_CCMP2467-aa-gen	yes	Genome	Symbiodinium			4.250	4.250	4.250	[158]	yes	[306]	808.23000	43403		[307]	JGI	Symbiodinium microadriaticum CCMP2467	https://mycocosm.jgi.doe.gov/Symmic1/Symmic1.home.html	29.00000	34.750000	[158]
(Symbiodinium) Fugacium	kawagutii		Symbiodinium_kawagutii-aa-gen	yes	Genome	Symbiodinium			4.250	4.250	4.250	[158]	yes	[213]	1180.00000	36850		[308]	MALAB	Sequences: proteins	http://web.malab.cn/symka_new/download.jsp
Symbiodinium	tridacnidorum		Symbiodinium_tridacnidorum-aa-gen	yes	Genome	Symbiodinium			4.550	4.550	5.550	[@ leeSymbiodiniumTridacnidorumSp2015]	yes	[309]	766.60000	69018		[264]	MGU	symA3_37.fasta.gz	https://marinegenomics.oist.jp/symb/viewer/download?project_id=37
Symbiodinium	tridacnidorum		Symbiodinium_tridacnidorum-dna-trans	yes	Transcriptome	Symbiodinium			4.550	4.550	5.550	[@ leeSymbiodiniumTridacnidorumSp2015]	yes	[309]	1.00000	0		[264]	MGU	syma_transcriptome_37.fasta.gz	https://marinegenomics.oist.jp/symb/viewer/download?project_id=37
Ostreococcus	lucimarinus	CCE9901	Ostreococcus_lucimarinus_CCE9901-aa-gen	yes	Genome	Green			0.500	0.500	1.250	[158]	no	[188]	13.20000	7651		[188]	JGI	1077109	https://genome.jgi.doe.gov/portal/Ostnus_FD/Ostnus_FD.info.html	32.90000	-117.255000	[188]	0	[187]
Ostreococcus	lucimarinus	CCE9901	Ostreococcus_lucimarinus_CCE9901-dna-trans	yes	Transcriptome	Green			0.500	0.500	1.250	[158]	no	[188]	1.00000	0		[188]	JGI	1077109	https://genome.jgi.doe.gov/portal/Ostnus_FD/Ostnus_FD.info.html	32.90000	-117.255000	[188]	0	[187]
Ostreococcus	sp.	RCC809	Ostreococcus_sp_RCC809-aa-gen	yes	Genome	Green			1.000	1.000	1.000	[187]	no	[188]	13.30000	7492			JGI	16233	https://mycocosm.jgi.doe.gov/OstRCC809_2/OstRCC809_2.home.html	21.03000	-31.130000	[187]	0	[187]
Ostreococcus	sp.	RCC809	Ostreococcus_sp_RCC809-dna-trans	yes	Transcriptome	Green			1.000	1.000	1.000	[187]	no	[188]	1.00000	0			JGI	16233	https://mycocosm.jgi.doe.gov/OstRCC809_2/OstRCC809_2.home.html	21.03000	-31.130000	[187]	0	[187]
Micromonas	commoda	RCC299	Micromonas_commoda_RCC299-aa-gen	yes	Genome	Green			1.000	1.000	1.000	[187]	yes	[310]	21.10930	10137		[194]	NCBI	GCA_000090985.2	https://bioinformatics.psb.ugent.be/plaza/versions/pico-plaza/download	-22.33000	166.330000	[187]	0	[311]
Micromonas	commoda	RCC299	Micromonas_commoda_RCC299-dna-trans	yes	Transcriptome	Green			1.000	1.000	1.000	[187]	yes	[310]	1.00000	0		[194]	NCBI	GCA_000090985.2	https://bioinformatics.psb.ugent.be/plaza/versions/pico-plaza/download	-22.33000	166.330000	[187]	0	[311]
Pavlovales	sp.	CCMP2436	Pavlovales_sp_CCMP2436-aa-gen	yes	Genome	Haptophyte			3.750	3.750	5.000	[158]	yes	https://phycocosm.jgi.doe.gov/Pavlov2436_1/Pavlov2436_1.home.html	165.41000	26034			JGI	Pavlovales sp. CCMP2436 v1.0: Project: 1014533, Pavlov2436_1_GeneCatalog_proteins_20160817.aa.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Pavlov2436_1	76.32080	-75.817200	[158]
Pavlovales	sp.	CCMP2436	Pavlovales_sp_CCMP2436-dna-trans	yes	Transcriptome	Haptophyte			3.750	3.750	5.000	[158]	yes	https://phycocosm.jgi.doe.gov/Pavlov2436_1/Pavlov2436_1.home.html	1.00000	0			JGI	Pavlovales sp. CCMP2436 v1.0: Project: 1014533, Pavlov2436_1_GeneCatalog_transcripts_20160817.nt.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Pavlov2436_1	76.32080	-75.817200	[158]
Ochromonadaceae	sp.	CCMP2298	Ochromonadaceae_sp_CCMP2298-aa-gen	yes	Genome	Chrysophyte			5.750	5.750	5.750	[158]	yes	https://phycocosm.jgi.doe.gov/Ochro2298_1/Ochro2298_1.home.html	61.40000	20195		[312]	JGI	Ochromonadaceae sp. CCMP2298 v1.0	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Ochro2298_1	77.00140	-77.238300	[158]
Ochromonadaceae	sp.	CCMP2298	Ochromonadaceae_sp_CCMP2298-dna-trans	yes	Transcriptome	Chrysophyte			5.750	5.750	5.750	[158]	yes	https://phycocosm.jgi.doe.gov/Ochro2298_1/Ochro2298_1.home.html	1.00000	0		[312]	JGI	Ochromonadaceae sp. CCMP2298 v1.0	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Ochro2298_1	77.00140	-77.238300	[158]
Pelagomonas	calceolata	CCMP1756	Pelagomonas_calceolata_CCMP1756-aa-trans	yes	Transcriptome	Pelagophyte			1.000	1.000	1.500	[158]	yes	[198]	1.00000	19184		[176]	iMicrobe	Pelagomonas-calceolata-CCMP1756.pep.fa.gz	ftp://ftp.imicrobe.us/camera/combined_assemblies/	30.83330	-136.833300	[158]	0	[243]
Chrysochromulina	polylepis	CCMP1757	Chrysochromulina_polylepis_CCMP1757-aa-trans	yes	Transcriptome	Haptophyte			2.750	2.750	3.500	[158]	yes		1.00000	0		[176]	iMicrobe	Chrysochromulina-polylepis-CCMP1757/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Chrysochromulina-polylepis-CCMP1757/	64.75000	21.333300	[158]
Dunaliella	tertiolecta	CCMP1320	Dunaliella_tertiolecta_CCMP1320-aa-trans	yes	Transcriptome	Green			3.750	3.750	3.750	[158]	yes	[226]	1.00000	17597		[176]	iMicrobe	Dunaliella-tertiolecta-CCMP1320/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Dunaliella-tertiolecta-CCMP1320/
Goniomonas	pacifica	CCMP1869	Goniomonas_pacifica_CCMP1869-aa-trans	yes	Transcriptome	Cryptophyte			2.500	2.500	3.750	[158]	yes		1.00000	57820		[176]	iMicrobe	Goniomonas-pacifica-CCMP1869/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Goniomonas-pacifica-CCMP1869/	-37.86000	144.930000	[158]
Karenia	brevis	CCMP2229	Karenia_brevis_CCMP2229-aa-trans	yes	Transcriptome	Dinoflagellate			11.000	11.000	12.000	[158]	yes	[213]	1.00000	95332		[176]	iMicrobe	Karenia-brevis-CCMP2229/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Karenia-brevis-CCMP2229/	27.01710	-82.476300	[158]		[313]
Karlodinium	micrum	CCMP2283	Karlodinium_micrum_CCMP2283-aa-trans	yes	Transcriptome	Dinoflagellate			4.500	4.500	6.500	[158]	yes	[213]	1.00000	72309		[176]	iMicrobe	Karlodinium-micrum-CCMP2283/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Karlodinium-micrum-CCMP2283/	32.21670	-80.735500	[158]
Micromonas	polaris	CCMP2099	Micromonas-polaris-CCMP2099-aa-trans	yes	Transcriptome	Green			1.000	1.000	1.250	[158]	yes		1.00000	10163		[176]	iMicrobe	Micromonas-sp-CCMP2099/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Micromonas-sp-CCMP2099/	76.28330	-74.750000	[158]	0	[187]
Nitzschia	punctata	CCMP561	Nitzschia_punctata_CCMP561-aa-trans	yes	Transcriptome	Diatom	Pennate	[158]	2.750	2.750	3.500	[158]	no	[166]	1.00000	21173		[176]	iMicrobe	Nitzschia-punctata-CCMP561/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Nitzschia-punctata-CCMP561/	32.99000	-117.255000	[158]
Ochromonas	sp.	CCMP1393	Ochromonas_sp_CCMP1393-aa-gen	yes	Genome	Chrysophyte			2.500	2.500	2.500	[158]	yes		56.49000	19713			JGI	Ochromonas sp. CCMP1393 v1.4: Project: 1070490, Ochro1393_1_4_GeneCatalog_proteins_20181204.aa.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Ochro1393_1_4	38.70200	-72.366700	[158]
Ochromonas	sp.	CCMP1393	Ochromonas_sp_CCMP1393-aa-trans	yes	Transcriptome	Chrysophyte			2.500	2.500	2.500	[158]	yes		1.00000	21479		[176]	iMicrobe	Ochromonas-sp-CCMP1393/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Ochromonas-sp-CCMP1393/	38.70200	-72.366700	[158]
Pavlova	sp.	CCMP459	Pavlova_sp_CCMP459-aa-trans	yes	Transcriptome	Haptophyte			2.250	2.250	3.000	[158]	yes		1.00000	19266		[176]	iMicrobe	Pavlova-sp-CCMP459/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Pavlova-sp-CCMP459/	38.70200	-72.366700	[158]	0	[187]
Pleurochrysis	carterae	CCMP645	Pleurochrysis_carterae_CCMP645-aa-trans	yes	Transcriptome	Haptophyte			5.000	5.000	5.000	[158]	no		1.00000	39174		[176]	iMicrobe	Pleurochrysis-carterae-CCMP645/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Pleurochrysis-carterae-CCMP645/	41.52500	-70.673600	[158]
Prorocentrum	minimum	CCMP1329	Prorocentrum_minimum_CCMP1329-aa-trans	yes	Transcriptome	Dinoflagellate			5.500	5.500	65.750	[158]	yes	[213]	1.00000	96684		[176]	iMicrobe	Prorocentrum-minimum-CCMP1329/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Prorocentrum-minimum-CCMP1329/	40.66670	-73.250000	[158]	0	[187]
Prorocentrum	minimum	CCMP2233	Prorocentrum_minimum_CCMP2233-aa-trans	yes	Transcriptome	Dinoflagellate			9.000	9.000	9.500	[158]	yes	[213]	1.00000	88621		[176]	iMicrobe	Prorocentrum-minimum-CCMP2233/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Prorocentrum-minimum-CCMP2233/	38.59000	-75.100000	[158]	0	[187]
Rhodella	maculata	CCMP736	Rhodella_maculata_CCMP736-aa-trans	yes	Transcriptome	Red			5.750	5.750	5.750	[158]	no		1.00000	20890		[176]	iMicrobe	Rhodella-maculata-CCMP736/	ftp://ftp.imicrobe.us/camera/combined_assemblies/Rhodella-maculata-CCMP736/	51.53200	0.700000	[158]
Paraphysomonas	imperforata	CCMP1604	Paraphysomonas_imperforata_CCMP1604-aa-gen	yes	Genome	Chrysophyte			3.250	3.250	3.250	[158]	yes	[314]	67.19000	17326	JGI		JGI	Paraphysomonas imperforata CCMP1604 v1.4: Project: 1011391, Parimp1_4_GeneCatalog_proteins_20180208.aa.fasta.gz	https://phycocosm.jgi.doe.gov/Parimp1_4/Parimp1_4.home.html	22.75000	-158.000000	[158]
Paraphysomonas	imperforata	CCMP1604	Paraphysomonas_imperforata_CCMP1604-dna-trans	yes	Transcriptome	Chrysophyte			3.250	3.250	3.250	[158]	yes	[314]	1.00000	0	JGI		JGI	Paraphysomonas imperforata CCMP1604 v1.4: Project: 1011391, Parimp1_4_GeneCatalog_transcripts_20180208.nt.fasta.gz	https://phycocosm.jgi.doe.gov/Parimp1_4/Parimp1_4.home.html	22.75000	-158.000000	[158]
Chattonella	antiqua		Chattonella_antiqua-aa-trans	yes	Transcriptome	Raphidophyte			14.000	14.000	48.000	[315]	no	[315]	1.00000	39031		[316]	NIBB	Translated contigs	http://hab.nibb.ac.jp/
Heterocapsa	circularisquama		Heterocapsa_circularisquama-aa-trans	yes	Transcriptome	Dinoflagellate			8.650	8.650	11.950	[317]	yes	[213]	1.00000	71125		[316]	NIBB	Translated contigs	http://hab.nibb.ac.jp/
Seminavis	robusta	D6	Seminavis_robusta_D6-aa-gen	yes	Genome	Diatom	Pennate	[318]	3.000	3.000	15.000	[318]	no	[318]	125.57000	37455	JGI	[319]	JGI	Seminavis robusta D6	Seminavis robusta D6: Semro1_GeneCatalog_proteins_20200811.aa.fasta.gz
Baffinella	sp.	CCMP2293	Cryptophyceae_sp_CCMP2293-aa-gen	yes	Genome	Cryptophyte			2.250	2.250	4.500	[158]	yes		534.37000	33051		[312]	JGI	Cryptophyceae sp. CCMP2293 v1.0	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Crypto2293_1	78.59220	-74.492200	[158]
Baffinella	sp.	CCMP2293	Cryptophyceae_sp_CCMP2293-dna-trans	yes	Transcriptome	Cryptophyte			2.250	2.250	4.500	[158]	yes		1.00000	0		[312]	JGI	Cryptophyceae sp. CCMP2293 v1.0	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Crypto2293_1	78.59220	-74.492200	[158]
Nitzschia	inconspicua	GAI-293	Nitzschia_inconspicua_GAI293-aa-gen	yes	Genome	Diatom	Pennate	[185]	2.000	2.000	3.750	[185]	no	[166]	99.71000	38785		[185]	NCBI	GCA_019154785.2	https://www.ncbi.nlm.nih.gov/genome/104419
Nitzschia	inconspicua	GAI-293	Nitzschia_inconspicua_GAI293-dna-trans	yes	Transcriptome	Diatom	Pennate	[185]	2.000	2.000	3.750	[185]	no	[166]	1.00000	0		[185]	JGI	Nitzschia inconspicua GAI-293 v2.0: Nithil2_ExternalModels_transcripts_20201125.nt.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Nithil2
Kryptoperidinium	foliaceum	CCMP1326	Kryptoperidinium_foliaceum_CCMP1326-aa-trans	yes	Transcriptome	Dinoflagellate			12.250	12.250	13.250	[320]	yes	[213]	1.00000	172694		[176]	iMicrobe	Kryptoperidinium-foliaceum-CCMP1326.pep.fa	ftp://ftp.imicrobe.us/camera/combined_assemblies/	32.83000	-117.270000	[321]
Thalassionema	nitzschioides	L26_B	Thalassionema_nitzschioides_L26_B-aa-trans	yes	Transcriptome	Diatom	Pennate	[175]	2.500	2.750	30.000	[175]	no	[166]	1.00000	19904		[176]	iMicrobe	Thalassionema-nitzschioides-L26_B.pep	ftp://ftp.imicrobe.us/camera/combined_assemblies/				1	[300]
Picochlorum	sp.	SENEW3	Picochlorum_sp._SENEW3-aa-gen	yes	Genome	Green			1.250	1.250	1.250	[322]	no		13.47000	7014		[323]	Cyanophora	Picochlorum_SENEW3_v2.0	http://cyanophora.rutgers.edu/picochlorum/	33.00000	-117.270000		0	[187]	Also known as Picochlorum SE3
Picochlorum	oculata	UTEXLB1998	Picochlorum_oculata_UTEXLB1998-aa-gen	yes	Genome	Green			1.000	1.000	1.000	[324]	no	[324]	14.52000	6340		[323]	Cyanophora	Picochlorum_oculata	http://cyanophora.rutgers.edu/picochlorum/	37.24000	-76.500000
Picochlorum	sp.	NBRC102739	Picochlorum_sp._NBRC102739-aa-gen	yes	Genome	Green			1.250	1.250	1.250	[322]	no		22.76000	12018		[323]	Cyanophora	Picochlorum_NBRC102739	http://cyanophora.rutgers.edu/picochlorum/				0	[187]	Formerly known as Picochlorum (Nannochloris) MBIC10091
Diacronema	lutheri	NIVA-4/92	Diacronema_lutheri_NIVA492-aa-gen	yes	Genome	Haptophyte			2.500	2.500	2.500	[325]	yes	[325]	30.88910	14446		[325]	NCBI	MSCA_Paluth_1.1	https://www.ncbi.nlm.nih.gov/genome/97098	59.29000	10.569000
Chaetoceros	tenuissimus	NIES-3715	Chaetoceros_tenuissimus_NIES3715-aa-gen	yes	Genome	Diatom	Centric		2.500	2.500	2.500	[326]	no		41.15380	18866		[326]	NCBI	Cten210_1.0	https://www.ncbi.nlm.nih.gov/genome/110089	34.62889	135.035250		0
Vitrella	brassicaformis	CCMP3155	Vitrella_brassicaformis_CCMP3155-aa-gen	yes	Genome	Chromerid			12.500	12.500	12.500	[158]	yes	[327]	72.70000	23034		[328]	NCBI	GCA_001179505.1	https://www.ncbi.nlm.nih.gov/genome/13390	-23.50000	152.000000	[158]	1	[329]
Chromera	velia	CCMP2878	Chromera_velia_CCMP2878-aa-gen	yes	Genome	Chromerid			3.000	3.000	3.000	[158]	yes	https://www.nies.go.jp/chiiki1/protoz/morpho/flagella/chromera.htm	193.89000	24133		[328]	JGI	Chromera velia CCMP2878: Chrveli1_GeneCatalog_proteins_20200809.aa.fasta.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Chrveli1	-33.84410	151.278900	[158]
Chloropicon	primus	CCMP1205	Chloropicon_primus_CCMP1205-aa-gen	yes	Genome	Green			2.000	2.000	2.000	[158]	no	[330]	17.40000	8327		[330]	JGI	Chloropicon primus CCMP1205: Chlpri1_GeneCatalog_genes_20200307.gff.gz	https://genome.jgi.doe.gov/portal/pages/dynamicOrganismDownload.jsf?organism=Chlpri1

Table 5: Comparison of Manual and Automated Gene Counts

Ome	Genus	species	ProdOrScav	ROSEnzymeName	ROSEnzymeAbbrev	Manual_count	Automated_count
Fragilariopsis_cylindrus_CCMP1102-aa-gen	Fragilariopsis	cylindrus	Scavenging	Ascorbate peroxidase	APX	4	4
Fragilariopsis_cylindrus_CCMP1102-aa-gen	Fragilariopsis	cylindrus	Scavenging	Catalase	CAT	0	0
Fragilariopsis_cylindrus_CCMP1102-aa-gen	Fragilariopsis	cylindrus	Scavenging	Cytochrome C peroxidase	CCP	2	3
Fragilariopsis_cylindrus_CCMP1102-aa-gen	Fragilariopsis	cylindrus	Scavenging	Dehydroascorbate reductase	DHAR	1	0
Fragilariopsis_cylindrus_CCMP1102-aa-gen	Fragilariopsis	cylindrus	Scavenging	Glutathione peroxidase	GPx	4	6
Fragilariopsis_cylindrus_CCMP1102-aa-gen	Fragilariopsis	cylindrus	Scavenging	Glutathione reductase	GR	2	1
Fragilariopsis_cylindrus_CCMP1102-aa-gen	Fragilariopsis	cylindrus	Scavenging	Catalase peroxidase	Katg	2	2
Fragilariopsis_cylindrus_CCMP1102-aa-gen	Fragilariopsis	cylindrus	Scavenging	Monodehydroascorbate reductase	MDHAR	0	0
Fragilariopsis_cylindrus_CCMP1102-aa-gen	Fragilariopsis	cylindrus	Scavenging	Peroxiredoxin	Prxns	7	6
Fragilariopsis_cylindrus_CCMP1102-aa-gen	Fragilariopsis	cylindrus	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	3	5
Guillardia_theta_CCMP2712-aa-gen	Guillardia	theta	Scavenging	Ascorbate peroxidase	APX	4	3
Guillardia_theta_CCMP2712-aa-gen	Guillardia	theta	Scavenging	Catalase	CAT	0	1
Guillardia_theta_CCMP2712-aa-gen	Guillardia	theta	Scavenging	Cytochrome C peroxidase	CCP	2	4
Guillardia_theta_CCMP2712-aa-gen	Guillardia	theta	Scavenging	Dehydroascorbate reductase	DHAR	1	3
Guillardia_theta_CCMP2712-aa-gen	Guillardia	theta	Scavenging	Glutathione peroxidase	GPx	3	3
Guillardia_theta_CCMP2712-aa-gen	Guillardia	theta	Scavenging	Glutathione reductase	GR	2	0
Guillardia_theta_CCMP2712-aa-gen	Guillardia	theta	Scavenging	Catalase peroxidase	Katg	1	0
Guillardia_theta_CCMP2712-aa-gen	Guillardia	theta	Scavenging	Monodehydroascorbate reductase	MDHAR	0	0
Guillardia_theta_CCMP2712-aa-gen	Guillardia	theta	Scavenging	Peroxiredoxin	Prxns	8	4
Guillardia_theta_CCMP2712-aa-gen	Guillardia	theta	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	7	6
Phaeodactylum_tricornutum_CCAP10551-aa-gen	Phaeodactylum	tricornutum	Scavenging	Ascorbate peroxidase	APX	5	4
Phaeodactylum_tricornutum_CCAP10551-aa-gen	Phaeodactylum	tricornutum	Scavenging	Catalase	CAT	1	1
Phaeodactylum_tricornutum_CCAP10551-aa-gen	Phaeodactylum	tricornutum	Scavenging	Cytochrome C peroxidase	CCP	4	2
Phaeodactylum_tricornutum_CCAP10551-aa-gen	Phaeodactylum	tricornutum	Scavenging	Dehydroascorbate reductase	DHAR	1	0
Phaeodactylum_tricornutum_CCAP10551-aa-gen	Phaeodactylum	tricornutum	Scavenging	Glutathione peroxidase	GPx	3	3
Phaeodactylum_tricornutum_CCAP10551-aa-gen	Phaeodactylum	tricornutum	Scavenging	Glutathione reductase	GR	2	2
Phaeodactylum_tricornutum_CCAP10551-aa-gen	Phaeodactylum	tricornutum	Scavenging	Catalase peroxidase	Katg	1	1
Phaeodactylum_tricornutum_CCAP10551-aa-gen	Phaeodactylum	tricornutum	Scavenging	Monodehydroascorbate reductase	MDHAR	0	0
Phaeodactylum_tricornutum_CCAP10551-aa-gen	Phaeodactylum	tricornutum	Scavenging	Peroxiredoxin	Prxns	8	4
Phaeodactylum_tricornutum_CCAP10551-aa-gen	Phaeodactylum	tricornutum	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	3	3
Polarella_glacialis_CCMP1383-aa-gen	Polarella	glacialis	Scavenging	Ascorbate peroxidase	APX	18	17
Polarella_glacialis_CCMP1383-aa-gen	Polarella	glacialis	Scavenging	Catalase	CAT	0	0
Polarella_glacialis_CCMP1383-aa-gen	Polarella	glacialis	Scavenging	Cytochrome C peroxidase	CCP	4	4
Polarella_glacialis_CCMP1383-aa-gen	Polarella	glacialis	Scavenging	Dehydroascorbate reductase	DHAR	0	0
Polarella_glacialis_CCMP1383-aa-gen	Polarella	glacialis	Production	Glycolate oxidase	GlyOx	0	0
Polarella_glacialis_CCMP1383-aa-gen	Polarella	glacialis	Scavenging	Glutathione peroxidase	GPx	5	4
Polarella_glacialis_CCMP1383-aa-gen	Polarella	glacialis	Scavenging	Glutathione reductase	GR	3	2
Polarella_glacialis_CCMP1383-aa-gen	Polarella	glacialis	Scavenging	Catalase peroxidase	Katg	7	6
Polarella_glacialis_CCMP1383-aa-gen	Polarella	glacialis	Scavenging	Monodehydroascorbate reductase	MDHAR	0	0
Polarella_glacialis_CCMP1383-aa-gen	Polarella	glacialis	Production	Nitric oxide synthase	NOS	0	1
Polarella_glacialis_CCMP1383-aa-gen	Polarella	glacialis	Scavenging	Peroxiredoxin	Prxns	15	13
Polarella_glacialis_CCMP1383-aa-gen	Polarella	glacialis	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	21	19
Polarella_glacialis_CCMP1383-aa-gen	Polarella	glacialis	Production	Sulfite oxidase	SulOx	4	4
Polarella_glacialis_CCMP2088-aa-gen	Polarella	glacialis	Scavenging	Ascorbate peroxidase	APX	12	12
Polarella_glacialis_CCMP2088-aa-gen	Polarella	glacialis	Scavenging	Catalase	CAT	0	0
Polarella_glacialis_CCMP2088-aa-gen	Polarella	glacialis	Scavenging	Cytochrome C peroxidase	CCP	4	4
Polarella_glacialis_CCMP2088-aa-gen	Polarella	glacialis	Scavenging	Dehydroascorbate reductase	DHAR	0	0
Polarella_glacialis_CCMP2088-aa-gen	Polarella	glacialis	Scavenging	Glutathione peroxidase	GPx	5	4
Polarella_glacialis_CCMP2088-aa-gen	Polarella	glacialis	Scavenging	Glutathione reductase	GR	4	4
Polarella_glacialis_CCMP2088-aa-gen	Polarella	glacialis	Scavenging	Catalase peroxidase	Katg	7	5
Polarella_glacialis_CCMP2088-aa-gen	Polarella	glacialis	Scavenging	Monodehydroascorbate reductase	MDHAR	0	0
Polarella_glacialis_CCMP2088-aa-gen	Polarella	glacialis	Scavenging	Peroxiredoxin	Prxns	18	13
Polarella_glacialis_CCMP2088-aa-gen	Polarella	glacialis	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	14	14
Pseudo-nitzschia_multistriata_B856-aa-gen	Pseudo-nitzschia	multistriata	Scavenging	Ascorbate peroxidase	APX	4	1
Pseudo-nitzschia_multistriata_B856-aa-gen	Pseudo-nitzschia	multistriata	Scavenging	Catalase	CAT	0	0
Pseudo-nitzschia_multistriata_B856-aa-gen	Pseudo-nitzschia	multistriata	Scavenging	Cytochrome C peroxidase	CCP	1	1
Pseudo-nitzschia_multistriata_B856-aa-gen	Pseudo-nitzschia	multistriata	Scavenging	Dehydroascorbate reductase	DHAR	1	0
Pseudo-nitzschia_multistriata_B856-aa-gen	Pseudo-nitzschia	multistriata	Production	Glycolate oxidase	GlyOx	2	0
Pseudo-nitzschia_multistriata_B856-aa-gen	Pseudo-nitzschia	multistriata	Scavenging	Glutathione peroxidase	GPx	0	0
Pseudo-nitzschia_multistriata_B856-aa-gen	Pseudo-nitzschia	multistriata	Scavenging	Glutathione reductase	GR	3	1
Pseudo-nitzschia_multistriata_B856-aa-gen	Pseudo-nitzschia	multistriata	Scavenging	Catalase peroxidase	Katg	1	0
Pseudo-nitzschia_multistriata_B856-aa-gen	Pseudo-nitzschia	multistriata	Production	Nitric oxide synthase	NOS	0	0
Pseudo-nitzschia_multistriata_B856-aa-gen	Pseudo-nitzschia	multistriata	Scavenging	Peroxiredoxin	Prxns	7	3
Pseudo-nitzschia_multistriata_B856-aa-gen	Pseudo-nitzschia	multistriata	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	3	5
Pseudo-nitzschia_multistriata_B856-aa-gen	Pseudo-nitzschia	multistriata	Production	Sulfite oxidase	SulOx	1	1
Symbiodinium_goreaui-aa-gen	(Symbiodinium) Cladocopium	goreaui	Scavenging	Ascorbate peroxidase	APX	11	7
Symbiodinium_goreaui-aa-gen	(Symbiodinium) Cladocopium	goreaui	Scavenging	Catalase	CAT	0	0
Symbiodinium_goreaui-aa-gen	(Symbiodinium) Cladocopium	goreaui	Scavenging	Cytochrome C peroxidase	CCP	3	2
Symbiodinium_goreaui-aa-gen	(Symbiodinium) Cladocopium	goreaui	Scavenging	Dehydroascorbate reductase	DHAR	1	2
Symbiodinium_goreaui-aa-gen	(Symbiodinium) Cladocopium	goreaui	Scavenging	Glutathione peroxidase	GPx	4	2
Symbiodinium_goreaui-aa-gen	(Symbiodinium) Cladocopium	goreaui	Scavenging	Glutathione reductase	GR	4	4
Symbiodinium_goreaui-aa-gen	(Symbiodinium) Cladocopium	goreaui	Scavenging	Catalase peroxidase	Katg	2	2
Symbiodinium_goreaui-aa-gen	(Symbiodinium) Cladocopium	goreaui	Scavenging	Monodehydroascorbate reductase	MDHAR	1	1
Symbiodinium_goreaui-aa-gen	(Symbiodinium) Cladocopium	goreaui	Scavenging	Peroxiredoxin	Prxns	12	8
Symbiodinium_goreaui-aa-gen	(Symbiodinium) Cladocopium	goreaui	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	4	8
Symbiodinium_kawagutii-aa-gen	(Symbiodinium) Fugacium	kawagutii	Scavenging	Ascorbate peroxidase	APX	18	16
Symbiodinium_kawagutii-aa-gen	(Symbiodinium) Fugacium	kawagutii	Scavenging	Catalase	CAT	0	0
Symbiodinium_kawagutii-aa-gen	(Symbiodinium) Fugacium	kawagutii	Scavenging	Cytochrome C peroxidase	CCP	1	0
Symbiodinium_kawagutii-aa-gen	(Symbiodinium) Fugacium	kawagutii	Scavenging	Glutathione peroxidase	GPx	1	1
Symbiodinium_kawagutii-aa-gen	(Symbiodinium) Fugacium	kawagutii	Scavenging	Glutathione reductase	GR	2	1
Symbiodinium_kawagutii-aa-gen	(Symbiodinium) Fugacium	kawagutii	Scavenging	Catalase peroxidase	Katg	3	1
Symbiodinium_kawagutii-aa-gen	(Symbiodinium) Fugacium	kawagutii	Scavenging	Monodehydroascorbate reductase	MDHAR	0	0
Symbiodinium_kawagutii-aa-gen	(Symbiodinium) Fugacium	kawagutii	Scavenging	Peroxiredoxin	Prxns	9	7
Symbiodinium_kawagutii-aa-gen	(Symbiodinium) Fugacium	kawagutii	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	7	5
Symbiodinium_minutum-aa-gen	(Symbiodinium) Breviolum	minutum	Scavenging	Ascorbate peroxidase	APX	16	14
Symbiodinium_minutum-aa-gen	(Symbiodinium) Breviolum	minutum	Scavenging	Catalase	CAT	0	0
Symbiodinium_minutum-aa-gen	(Symbiodinium) Breviolum	minutum	Scavenging	Cytochrome C peroxidase	CCP	7	1
Symbiodinium_minutum-aa-gen	(Symbiodinium) Breviolum	minutum	Scavenging	Dehydroascorbate reductase	DHAR	1	2
Symbiodinium_minutum-aa-gen	(Symbiodinium) Breviolum	minutum	Production	Glycolate oxidase	GlyOx	2	2
Symbiodinium_minutum-aa-gen	(Symbiodinium) Breviolum	minutum	Scavenging	Glutathione peroxidase	GPx	1	0
Symbiodinium_minutum-aa-gen	(Symbiodinium) Breviolum	minutum	Scavenging	Glutathione reductase	GR	5	5
Symbiodinium_minutum-aa-gen	(Symbiodinium) Breviolum	minutum	Scavenging	Catalase peroxidase	Katg	5	1
Symbiodinium_minutum-aa-gen	(Symbiodinium) Breviolum	minutum	Scavenging	Monodehydroascorbate reductase	MDHAR	2	2
Symbiodinium_minutum-aa-gen	(Symbiodinium) Breviolum	minutum	Production	Nitric oxide synthase	NOS	0	2
Symbiodinium_minutum-aa-gen	(Symbiodinium) Breviolum	minutum	Scavenging	Peroxiredoxin	Prxns	8	8
Symbiodinium_minutum-aa-gen	(Symbiodinium) Breviolum	minutum	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	9	5
Symbiodinium_minutum-aa-gen	(Symbiodinium) Breviolum	minutum	Production	Sulfite oxidase	SulOx	5	5
Symbiodiniun_tridacnidorum-aa-gen	Symbiodinium	tridacnidorum	Scavenging	Ascorbate peroxidase	APX	16	7
Symbiodiniun_tridacnidorum-aa-gen	Symbiodinium	tridacnidorum	Scavenging	Catalase	CAT	0	0
Symbiodiniun_tridacnidorum-aa-gen	Symbiodinium	tridacnidorum	Scavenging	Cytochrome C peroxidase	CCP	2	2
Symbiodiniun_tridacnidorum-aa-gen	Symbiodinium	tridacnidorum	Scavenging	Dehydroascorbate reductase	DHAR	0	0
Symbiodiniun_tridacnidorum-aa-gen	Symbiodinium	tridacnidorum	Scavenging	Glutathione peroxidase	GPx	3	2
Symbiodiniun_tridacnidorum-aa-gen	Symbiodinium	tridacnidorum	Scavenging	Glutathione reductase	GR	4	4
Symbiodiniun_tridacnidorum-aa-gen	Symbiodinium	tridacnidorum	Scavenging	Catalase peroxidase	Katg	4	1
Symbiodiniun_tridacnidorum-aa-gen	Symbiodinium	tridacnidorum	Scavenging	Monodehydroascorbate reductase	MDHAR	1	1
Symbiodiniun_tridacnidorum-aa-gen	Symbiodinium	tridacnidorum	Scavenging	Peroxiredoxin	Prxns	13	4
Symbiodiniun_tridacnidorum-aa-gen	Symbiodinium	tridacnidorum	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	11	4
Thalassiosira_antarctica_CCMP982-aa-trans	Thalassiosira	antarctica	Scavenging	Catalase	CAT	1	1
Thalassiosira_antarctica_CCMP982-aa-trans	Thalassiosira	antarctica	Scavenging	Cytochrome C peroxidase	CCP	2	4
Thalassiosira_antarctica_CCMP982-aa-trans	Thalassiosira	antarctica	Scavenging	Dehydroascorbate reductase	DHAR	0	0
Thalassiosira_antarctica_CCMP982-aa-trans	Thalassiosira	antarctica	Production	Glycolate oxidase	GlyOx	3	2
Thalassiosira_antarctica_CCMP982-aa-trans	Thalassiosira	antarctica	Scavenging	Glutathione peroxidase	GPx	6	5
Thalassiosira_antarctica_CCMP982-aa-trans	Thalassiosira	antarctica	Scavenging	Glutathione reductase	GR	6	3
Thalassiosira_antarctica_CCMP982-aa-trans	Thalassiosira	antarctica	Scavenging	Catalase peroxidase	Katg	3	2
Thalassiosira_antarctica_CCMP982-aa-trans	Thalassiosira	antarctica	Scavenging	Monodehydroascorbate reductase	MDHAR	0	0
Thalassiosira_antarctica_CCMP982-aa-trans	Thalassiosira	antarctica	Production	Nitric oxide synthase	NOS	2	5
Thalassiosira_antarctica_CCMP982-aa-trans	Thalassiosira	antarctica	Scavenging	Peroxiredoxin	Prxns	8	5
Thalassiosira_antarctica_CCMP982-aa-trans	Thalassiosira	antarctica	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	7	11
Thalassiosira_antarctica_CCMP982-aa-trans	Thalassiosira	antarctica	Production	Sulfite oxidase	SulOx	2	2
Thalassiosira_oceanica_CCMP1005-aa-gen	Thalassiosira	oceanica	Scavenging	Ascorbate peroxidase	APX	14	6
Thalassiosira_oceanica_CCMP1005-aa-gen	Thalassiosira	oceanica	Scavenging	Catalase	CAT	0	0
Thalassiosira_oceanica_CCMP1005-aa-gen	Thalassiosira	oceanica	Scavenging	Cytochrome C peroxidase	CCP	2	1
Thalassiosira_oceanica_CCMP1005-aa-gen	Thalassiosira	oceanica	Scavenging	Dehydroascorbate reductase	DHAR	0	0
Thalassiosira_oceanica_CCMP1005-aa-gen	Thalassiosira	oceanica	Production	Glycolate oxidase	GlyOx	3	4
Thalassiosira_oceanica_CCMP1005-aa-gen	Thalassiosira	oceanica	Scavenging	Glutathione peroxidase	GPx	7	6
Thalassiosira_oceanica_CCMP1005-aa-gen	Thalassiosira	oceanica	Scavenging	Glutathione reductase	GR	4	0
Thalassiosira_oceanica_CCMP1005-aa-gen	Thalassiosira	oceanica	Scavenging	Catalase peroxidase	Katg	4	4
Thalassiosira_oceanica_CCMP1005-aa-gen	Thalassiosira	oceanica	Scavenging	Monodehydroascorbate reductase	MDHAR	0	0
Thalassiosira_oceanica_CCMP1005-aa-gen	Thalassiosira	oceanica	Production	Nitric oxide synthase	NOS	1	3
Thalassiosira_oceanica_CCMP1005-aa-gen	Thalassiosira	oceanica	Scavenging	Peroxiredoxin	Prxns	7	10
Thalassiosira_oceanica_CCMP1005-aa-gen	Thalassiosira	oceanica	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	5	5
Thalassiosira_oceanica_CCMP1005-aa-gen	Thalassiosira	oceanica	Production	Sulfite oxidase	SulOx	4	3
Thalassiosira_pseudonana_CCMP1335-aa-gen	Thalassiosira	pseudonana	Scavenging	Ascorbate peroxidase	APX	7	6
Thalassiosira_pseudonana_CCMP1335-aa-gen	Thalassiosira	pseudonana	Scavenging	Catalase	CAT	0	0
Thalassiosira_pseudonana_CCMP1335-aa-gen	Thalassiosira	pseudonana	Scavenging	Cytochrome C peroxidase	CCP	0	0
Thalassiosira_pseudonana_CCMP1335-aa-gen	Thalassiosira	pseudonana	Scavenging	Dehydroascorbate reductase	DHAR	0	0
Thalassiosira_pseudonana_CCMP1335-aa-gen	Thalassiosira	pseudonana	Scavenging	Glutathione peroxidase	GPx	2	2
Thalassiosira_pseudonana_CCMP1335-aa-gen	Thalassiosira	pseudonana	Scavenging	Glutathione reductase	GR	3	2
Thalassiosira_pseudonana_CCMP1335-aa-gen	Thalassiosira	pseudonana	Scavenging	Catalase peroxidase	Katg	1	1
Thalassiosira_pseudonana_CCMP1335-aa-gen	Thalassiosira	pseudonana	Scavenging	Monodehydroascorbate reductase	MDHAR	0	0
Thalassiosira_pseudonana_CCMP1335-aa-gen	Thalassiosira	pseudonana	Scavenging	Peroxiredoxin	Prxns	6	8
Thalassiosira_pseudonana_CCMP1335-aa-gen	Thalassiosira	pseudonana	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	3	5
Thalassiosira_rotula_CCMP3096-aa-trans	Thalassiosira	rotula	Scavenging	Ascorbate peroxidase	APX	11	3
Thalassiosira_rotula_CCMP3096-aa-trans	Thalassiosira	rotula	Scavenging	Catalase	CAT	0	0
Thalassiosira_rotula_CCMP3096-aa-trans	Thalassiosira	rotula	Scavenging	Cytochrome C peroxidase	CCP	6	5
Thalassiosira_rotula_CCMP3096-aa-trans	Thalassiosira	rotula	Scavenging	Dehydroascorbate reductase	DHAR	0	0
Thalassiosira_rotula_CCMP3096-aa-trans	Thalassiosira	rotula	Production	Glycolate oxidase	GlyOx	2	1
Thalassiosira_rotula_CCMP3096-aa-trans	Thalassiosira	rotula	Scavenging	Glutathione peroxidase	GPx	6	3
Thalassiosira_rotula_CCMP3096-aa-trans	Thalassiosira	rotula	Scavenging	Glutathione reductase	GR	5	4
Thalassiosira_rotula_CCMP3096-aa-trans	Thalassiosira	rotula	Scavenging	Catalase peroxidase	Katg	4	1
Thalassiosira_rotula_CCMP3096-aa-trans	Thalassiosira	rotula	Scavenging	Monodehydroascorbate reductase	MDHAR	0	0
Thalassiosira_rotula_CCMP3096-aa-trans	Thalassiosira	rotula	Production	Nitric oxide synthase	NOS	2	5
Thalassiosira_rotula_CCMP3096-aa-trans	Thalassiosira	rotula	Scavenging	Peroxiredoxin	Prxns	8	3
Thalassiosira_rotula_CCMP3096-aa-trans	Thalassiosira	rotula	Scavenging	Superoxide Dismutase (Fe, Mn, Cu/Zn, Ni)	SOD	3	4
Thalassiosira_rotula_CCMP3096-aa-trans	Thalassiosira	rotula	Production	Sulfite oxidase	SulOx	3	3

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